Devices, methods, and systems of functional optical coherence tomography

ABSTRACT

The present disclosure provides systems and methods for the determining a rate of change of one or more analyte concentrations in a target using non invasive non contact imaging techniques such as OCT. Generally, OCT data is acquired and optical information is extracted from OCT scans to quantitatively determine both a flow rate of fluid in the target and a concentration of one or more analytes. Both calculations can provide a means to determine a change in rate of an analyte over time. Example methods and systems of the disclosure may be used in assessing metabolism of a tissue, where oxygen is the analyte detected, or other functional states, and be generally used for the diagnosis, monitoring and treatment of disease.

CROSS-REFERENCE

This application arises as a continuation of U.S. patent applicationSer. No. 15/465,285 filed on Mar. 21, 2017, entitled “DEVICES, METHODS,AND SYSTEMS OF FUNCTIONAL OPTICAL COHERENCE TOMOGRAPHY,” which claimsthe benefit of U.S. patent application Ser. No. 14/698,641 filed on Apr.28, 2015, entitled “DEVICES, METHODS, AND SYSTEMS OF FUNCTIONAL OPTICALCOHERENCE TOMOGRAPHY”, which claims the benefit of U.S. PatentApplication Ser. No. 61/985,278, filed on Apr. 28, 2014, each of whichare incorporated herein by reference in their entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH FOR DEVELOPMENT

This invention was made with government support under grant numbers 1RC4EY021357 and 1 R01EY019951 awarded by the National Institutes ofHealth; and grant numbers CBET-1055379 and CBET-1240416 awarded by theNational Science Foundation. The government has certain rights in theinvention.

BACKGROUND OF THE DISCLOSURE

Optical Coherence Tomography (OCT) is a non-invasive optical imagingtechnique which produces depth-resolved reflectance imaging of samplesthrough the use of a low coherence interferometer system. OCT imagingallows for three-dimensional (3D) visualization of structures in avariety of biological systems and non-biological systems not easilyaccessible through other imaging techniques. In some instances OCT mayprovide a non-invasive, non-contact means of assessing informationwithout disturbing or injuring a target or sample. In medicine forexample, OCT applications have included but are not limited tonon-invasive means of diagnosis of diseases in the retina of the eye,interventional cardiology treatment and assessment, and diagnostics ofskins lesion for dermatology.

Generally, OCT is used to generate 3D images of various structures,including vessels such as blood vasculature. Previously describedmethods of OCT provide methods for obtaining structural informationdirected at acquiring information about the size, shape, topology andphysical attributes of the outside structures of vessels. However,information regarding physical and chemical attributes inside vesselsand structures can also be useful, yielding more functional andpotentially useful information about a system.

In medical diagnostics for example, vascular visualization andquantitative information about attributes of blood can be important forthe diagnosis and treatment of many diseases. For example, approximately50% of Americans will get cancer and approximately 50% of those will diefrom cancer. In the example of ocular disease, such as diabeticretinopathy, age related macular degeneration (AMD), glaucoma, nearly 10million people in the U.S. and over 200 million people worldwide may beat risk for vision loss or blindness. It is suspected that vasculatureremodeling and biochemical pathways that affect abnormal morphology ofblood supplies in the eye and around tumors may be correlated with theonset and prognosis of these diseases, respectively. In some examples,an abnormal increase or decrease in metabolism, illustrated throughabnormal blood vessel proliferation may also correlate with disease.

Non-invasive methods that allow acquisition of information about tissueattributes related to the etiologies of diseases, may lead to preventionof such diseases. The ability to measure blood flow, and other variousbiochemical analytes within a blood flow, such as oxygen (pO₂), glucoseor other biomarkers can help indicate a functional state of targettissue, such as metabolic activity. In some examples, the ability tounderstand a functional state of a target tissue, can be useful fortreatment, monitoring or prevention of disease. This especially truewhen attributes such both as blood flow and oxygen can both be measured.Currently, there are no non-invasive three dimensional (3D) imagingtechniques to measure oxygen metabolism in vivo in tissues. There isneed in the art for improved methods and devices for non-invasive 3Dquantitative imaging of metabolism and other target functions for avariety of applications including but not limited to the treatment anddiagnosis of disease.

SUMMARY OF THE DISCLOSURE

In a first aspect, the present disclosure provides for a method forimaging a target, the method comprising performing optical coherencetomography (OCT) scanning on a target with one or more beams of lowcoherence light, wherein the one or more beams of light comprise one ormore wavelengths, acquiring optical information from reflected signalsgenerated by the OCT scanning, quantitatively 3D-imaging in the target,determining a flow rate of a fluid and a concentration of one or moreanalytes from the optical information acquired, and determining a rateof change of the one or more analyte concentrations in the target.

Another aspect of the present disclosure provides a method for thediagnosis or treatment of a disease in a subject, the method comprisingobtaining 3D OCT scans of a target; determining a status of one or moremolecular markers in a bodily fluid in the target, while simultaneouslyquantifying flow of the bodily fluid from the 3D scans generated; andproviding a medical decision. In some examples, OCT scans includesinvisible light, visible light or near-infrared (NIR) light.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of a device of this disclosure are set forth withparticularity in the appended claims. A better understanding of thefeatures and advantages of this disclosure will be obtained by referenceto the following detailed description that sets forth illustrativeexamples, in which the principles of a device of this disclosure areutilized, and the accompanying drawings of which:

FIG. 1a is an example in vivo B-scan image of a pigmented rat eye usinginversed contrast.

FIG. 1b is an example short time Fourier transform (STFT) OCT spectra.

FIG. 1c is an example STFT OCT extracted spectra, from the bottom of thevessel wall.

FIG. 1d is an example of reflection spectra from the bottom of thevessel.

FIG. 2a is an example schematic of a free space vis-OCT device.

FIG. 2b is an example illumination spectrum of a free space vis-OCTdevice.

FIG. 2c is an example of theoretical and axial resolutions of a freespace vis-OCT device.

FIG. 3 is an example schematic of dual beam scanning. The target isilluminated with one or beams concurrently or sequentially.

FIG. 4 is a schematic of an example fOCT device.

FIG. 5 is a schematic of an example fOCT device.

FIG. 6 is an example schematic of multi beam scanning. The target isilluminated with one or more beams concurrently or sequentially.

FIG. 7 is an example schematic of multi beam scanning with two or morebeams. The target is illuminated with one or more beams concurrently orsequentially.

FIG. 8 is a schematic of an example fOCT device.

FIG. 9 is a schematic of an example fOCT device.

FIG. 10a is an example vis-OCT fundus image. The white circular linerepresents the B-scan trajectory.

FIG. 10b is an example fused vascular image and oxygen map of majorvessels.

FIG. 10c is an example of a retinal B-scan.

FIG. 10d is a graph showing an example quantification of sO₂ for eachindividual vessel.

FIG. 10e is an example of average arterial and venous sO₂ values.

FIG. 11a is an example vis-OCT fundus image. The white circular linerepresents the B-scan trajectory.

FIG. 11b is an example B-scan.

FIG. 11c is an example phase shift B-scan image.

FIG. 11d is an example schematic and graph of measured Doppler angles.

FIG. 11e is an example graph of fitted blood flow velocity data.

FIG. 11f is an example graph of blood flow velocity data for arteriesand veins.

FIG. 11g is an example graph of total blood flow velocity data forarteries and veins.

FIG. 12 is a flow diagram of an example method for metabolic functionalOCT.

FIG. 13 is a flow schematic for an example process of quantitatively3D-imaging in the target, a flow rate of a fluid and a concentration ofoxygen, from optical information acquired and determining a rate ofchange of metabolism based on oxygen consumption.

FIG. 14 is a flow schematic for an example process of quantitatively3D-imaging in the target, a flow rate of a fluid and a concentration ofone or more analytes, from optical information acquired and determininga rate of change of the one or more analyte concentrations in thetarget.

FIG. 15a is a diagram showing an example flow contrast of moving cells.The phase shift of the complex reflectance signal is proportional to theflow velocity projected to the light beam.

FIG. 15b is a schematic of an example geometry for calculating a Dopplerangle.

FIG. 15c is an example B-scan.

FIG. 15d is an example of a phase shift B-scan.

FIG. 16a is an example fundus image with vis-OCT and the circular whiteline represents a B-scan trajectory.

FIG. 16b is an example B-scan indicating various histological layers ofthe retina.

FIG. 16c is an example B-scan showing individual vessels.

FIG. 17 is graph showing example differences in retinal flowmeasurements between major arterioles and veins in rats.

FIG. 18a is an example longitudinal stability study on sO₂.

FIG. 18b is an example longitudinal stability study on blood flow.

FIG. 18c is an example longitudinal stability study on rMRO₂.

FIG. 19 is a graph of example simulated oxygen tension PO₂ profiles asfunction of retinal depth. Retinal pigmented epithelium (RPE)/outersegment of photoreceptor (OS) layer (Layer 1), and the outer nuclearlayer (ONL)/outer plexiform layer (OPL) (Layer 3) has the linear profileof PO₂; while inner segment of photoreceptor (OS) (Layer 2) has aquadratic PO₂ profile. Solid line is the PO₂ profile under normal airbreathing, and the dashed line is under systemic hypoxia at PaO₂=72mmHg. The choroidal oxygen tension (Pc) is proportional to the systemicPaO₂. The oxygen tension at the interface between outer and inner retina(PL) is considered to be the same due to the autoregulation of theretinal circulation.

FIG. 20 is a schematic of an example vis-OCT device.

FIG. 21a is a representation of an example scanning pattern schematicfor flow measurement. Two concentric circular scans crossed all bloodvessels originating from the optic disk.

FIG. 21b is a graph of example pulsatile flow patterns with thesimultaneous EKG pattern.

FIG. 21c is a graph of an example Fourier transform of the pulsatileflow pattern.

FIG. 21d is a graph showing example correlation of arterial sO₂measurement by vis-OCT and spO₂ (pulse oximetry).

FIG. 21e is a graph of example arterial and venous sO₂ response to thechanging oxygen content of the inhaled air.

FIG. 22a illustrates example retinal vasculature changes under hypoxia.Mean intensity projection image around optic disk under normoxia.

FIG. 22b illustrates an example mean intensity projection image aroundoptic disk under normoxia.

FIG. 22c illustrates an example of average diameter of the majorarterioles (A) and veins (V) in normoxia and hypoxia.

FIG. 22d illustrates an example magnified view of the insert in FIG. 22a.

FIG. 22e illustrates an example magnified view of the insert in FIG. 22b.

FIG. 22f illustrates an example comparison of the arteriole diameterunder normoxia and hypoxia.

FIG. 23a reflects example retinal oxygen consumption derived fromretinal circulation and responds to systemic oxygen tension. FIG. 23aprovides an example schematic representation of the hypoxia protocol.The inhaled oxygen content was reduced gradually in six stages from 21%to 9%. Arterial and venous sO₂, blood flow, and blood vessel diameterwere measured at each step.

FIG. 23b illustrates example sO₂ changes under reduce oxygen content.

FIG. 23c illustrates example PO₂ changes under reduce oxygen content.

FIG. 23d illustrates an example corresponding progression ofarteriovenous oxygenation difference.

FIG. 23e illustrates an example average diameter of major retinal bloodvessels.

FIG. 23f illustrates an example retinal blood flow.

FIG. 23g illustrates an example of oxygen delivery from arterialvessels.

FIG. 23h illustrates an example oxygen extraction fraction.

FIG. 23i illustrates an example of retinal oxygen metabolism fromretinal circulation.

FIG. 24a shows an example schematic of oxygen supply balance changesbetween retinal and choroidal circulation under hypoxia. Under systemichypoxia, the retinal circulation provides more oxygen to the outerretina to compensate the deficit from choroidal circulation.

FIG. 24b shows an example anatomical structure of a rat retina.

FIG. 24c shows an example simulated PO₂ profile across the retina.

FIG. 24d shows an example graph of arterial PO2 versus O2 metabolicrate.

FIG. 25 illustrates a schematic of an example logical apparatus that canread instructions from media, connect to a network and store datagenerated by a fOCT device.

FIG. 26a illustrates example dynamic monitoring of mucus thickness usingOCT. FIG. 26a shows an example schematic diagram of a table-top vis-OCTsystem.

FIG. 26b illustrates an example schematic diagram and photograph of anexample endoscopic NIR-OCT probe.

FIG. 26c shows an example endocervical tissue sample/target imaged withan endoscopic NIR-OCT probe.

FIG. 26d shows an example endocervical tissue sample/target placed underan OCT objective lens.

FIG. 26e indicates an example process of performing 3-dimensionalendoscopic OCT scan. BS, beam splitter; DC, dispersion compensation; GM,galvanometer mirror; L, objective lens; M1, M2, reflective mirror; F,pigtailed fiber; FC, fiber coupler; GL, grin lens; P, prism; NIR, nearinfrared; OCT, optical coherence tomography; vis-OCT, visible-lightoptical coherence tomography.

FIG. 27a illustrates example dynamic monitoring of mucus layer thicknesschange during secretion and enzymatic hydrolysis. FIG. 27a includes asingle vis-OCT B-scan showing anatomical features of endocervicaltissue.

FIG. 27b shows an example graph of measured maximum mucus thickness whenincubated in PBS solution at 37 during a period of 40 minutes.

FIG. 27c shows an example graph of measured maximum mucus thicknessafter adding neuraminidase. The example of FIG. 27c was observed over aperiod of 15 minutes. **, P<0.01 comparing to Time=0. Arrow, surface ofmucus; E, epithelium; LP, lamina propria; vis-OCT, visible-light opticalcoherence tomography.

FIG. 28a shows an example endoscopic NIR-OCT imaging of intact macaquevagina ex vivo. (A) A 360° circular B-scan image of the vagina duct(Resealed. A scale bar indicates radius to the scanning axis, unit mm).

FIG. 28b shows an example high density angular scan covering 45° showingdetails of the vagina surface structure. As shown in the example of FIG.28b , a scale bar indicates 100 μm.

FIG. 28c shows an example 3-dimensional rendering of the same 45′circular scan with 0.8 mm longitudinal displacement, showing the roughstructure of the vagina epithelium. R, vaginal rugae; G, glass surfaceof protective shell; M, granular pattern indicates mucus, NIR, nearinfrared; OCT, optical coherence tomography.

FIG. 29 is a block diagram illustrating a first example architecture ofa computer system that can be used in connection with a fOCT device.

FIG. 30 is a diagram showing an example network with a plurality ofcomputer systems, and a plurality of cell phones and personal dataassistants configured with a fOCT device.

FIG. 31 is a block diagram of an example multiprocessor computer systemconfigured with a fOCT device.

The following detailed description of certain examples of the presentinvention will be better understood when read in conjunction with theappended drawings. For the purpose of illustrating the invention,certain examples are shown in the drawings. It should be understood,however, that the present invention is not limited to the arrangementsand instrumentality shown in the attached drawings.

DETAILED DESCRIPTION OF THE DISCLOSURE I. General Overview

The methods, devices and systems of the present disclosure provide forfunctional optical coherence tomography (fOCT). Generally, fOCT maycomprise a non-invasive, non-contact method for determining a functionalstate of target, such as the health of bodily tissue. In some examples,fOCT may be used for determining the change in metabolism of a tissue,therefore indicating something about disease state or health.

Generally, fOCT employs any method of OCT, as known in the art. fOCTprovides a method of extracting a full set of optical properties fromOCT spectra and simultaneously or substantially simultaneouslyextracting optical information to calculate flow rate of a fluid in atarget and a concentration of a particular analyte in the target. Insome examples, the same or single A-scan generated from OCT scans may beused for calculations of flow and analyte concentrations. For example,the target may be a human retina, where blood flow and oxygen may bedetermined or quantified using fOCT. In some examples, the target couldbe skin and the flow rate of sweat is calculated with a quantificationof glucose.

Generally, a schematic for determining metabolic rate is provided inFIG. 13 and provided for example. In some examples, interferometricdata, 1302, is acquired from OCT scans and converted to 3D complexreflectance data, 1304. This same A-scan data is then used to performsimultaneous, or substantially simultaneous calculations ordeterminations of flow and analyte concentrations. In some examples, 3Dvessel segmentation, 1306, spectral extraction, 1308 are performed toquantify oxygen saturation (sO₂), 1310. In some examples, this can beexpressed as partial pressure of oxygen, pO₂. Simultaneously, circularbrightness scan (B-scan) variance, 1312, and projected velocity, 1314,and microvasculature visualization, 1322, are used determined flow rateof blood. Simultaneously, circular B-scan amplitude, 1316, blood vesseldiameter, 1318 and blood vessel directionality, 1320 may be used todetermine absolute flow, 1324. Taken together, these calculations canhelp determine an accurate change in oxygen consumption in a tissue, oroverall oxygen metabolic rate, 1326.

In some examples, the accurate quantification of a flow parameter and ananalyte concentration can be used to determine a change in state oftarget function. For example, a change in metabolism or oxygenconsumption of the human retina may indicate retinal disease. In theexample of skin monitoring and glucose in sweat, blood glucose levelsfor diabetic monitoring may be performed using the methods, devices andsystems of the disclosure.

Given the label-free, non-invasive, non-contact methods of thedisclosure, a variety of medical applications may be employed includingthe disease monitoring and diagnosis of cancer and variety of otherocular diseases.

In some examples, the quantitatively 3D-imaging in the target isperformed without contacting at least one analyte with an exogenousreagent or label. In some examples, the one or more beams of lightcomprise, invisible light, visible light or near-infrared (NIR) light.In some examples OCT scanning generates one or more A-scans (amplitudemodulation scans).

In another aspect of the present disclosure, quantitatively imaging aflow rate of a fluid in the target and a concentration of one or moreanalytes in the fluid in the target, and the determining rate of changeof one more analyte concentrations use spectral analysis of the sameA-scan. In some examples, amplitude, intensity or phase, of the same OCTA-scan, are used for determining a rate of change of the one or moreanalyte concentrations. In some examples, the flow rate, theconcentration of one or more analytes, and the determining the rate ofchange or one or more analyte concentrations uses a plurality of OCTA-scans of the target.

In another aspect of the present disclosure, OCT is performed on aplurality of areas in the target. In some examples, one or more beams oflight are used to perform multi-beam or multi-band scanning OCT. In someexamples, a light source used for the illuminating is configured to havea power of at most 1.0 mW. In some examples, one or more beams of lightilluminate the target concurrently or sequentially. In some examples,quantitatively imaging a flow rate of a fluid in the target and aconcentration of one or more analytes in the fluid in the target occursubstantially simultaneously. In some examples, one or more beams oflight illuminate the target in a circular pattern or two or moreconcentric circular patterns.

In another aspect of the disclosure, the target is selected from thegroup consisting of tissue, healthy tissue, diseased tissue, retina,tumor, cancer, growth, fibroid, lesion, skin, mucosal lining, organ,graft, blood supply and one or more blood vessels. In some examples,quantitatively imaging a flow rate of a fluid in the target is performedusing near-infrared (NIR) light. In some examples, quantitativelyimaging a concentration of one or more analytes in the fluid in thetarget is performed using visible light.

In another aspect of the disclosure, the fluid may include but is notlimited to whole blood, blood plasma, blood serum, urine, semen, tears,sweat, saliva, lymph fluid, pleural effusion, peritoneal fluid, meningalfluid, amniotic fluid, glandular fluid, spinal fluid, conjunctivalfluid, vitreous, aqueous, vaginal fluid, bile, mucus, sputum andcerebrospinal fluid. In another aspect of the disclosure, the analyte isselected from the group consisting of oxygen, hemoglobin, oxygenatedhemoglobin, deoxygenated hemoglobin, glucose, sugar, blood areanitrogen, lactate, hematocrit, biomarker and nucleic acid.

In another aspect of the disclosure, determining the rate of change ofone or more analytes is performed by comparing or using a reference. Insome examples, the reference is healthy tissue. In some examples, thereference is the target in which the flow rate of a fluid and theconcentration of one or more analytes have been previously beenquantified. In some examples, one or more images of the target aregenerated. In some examples, the one or more images and the change inrate of analyte concentration are used to calculate a function of thetarget or a change in the function of the target. In some examples, thefunction of the target is a pathological alteration in a tissue. In someexamples, the function of the target is metabolic function. In someexamples, arteries and veins are determined in the one or more images.In some examples, the metabolic function is calculated in one or moreareas of the target. In another aspect of the disclosure, an exogenousagent is contacted with the target. In some examples, the exogenousagent is a contrast reagent. In some examples, the quantifying a flowrate of a fluid in the target comprises determining the cross sectionalarea of one or more vessels containing the fluid.

In another aspect of the disclosure, a medical decision is made bydetermining the rate of change of the one or more analyte concentrationsin the target.

In another aspect of the disclosure, spectral analysis is performed toextract a full set of optical properties of the target.

In another aspect of the disclosure, the method is configured for adevice selected from the group consisting of probe, handheld device,wearable device, endoscope, catheter probe, laparoscopic tool, surgicaltool, and needle.

Another aspect of the disclosure provides determining a status of one ormore molecular markers comprises calculating metabolic activity or achange in metabolic activity in the target. In some examples,determining a status of one or more molecular markers in a bodily fluidin the target is performed by measuring an intensity, amplitude or phaseof visible light reflected at a plurality of depths for each of aplurality of areas generated. In some examples, quantifying flow of thebodily fluid includes measuring an intensity, amplitude or phase of NIRlight reflected at a plurality of depths for each of a plurality ofareas generated.

In another aspect of the disclosure, one or more A-scans are obtained.In some examples, flow rate and the status of one or more molecularmarkers are determined using spectral analysis of the same A-scan. Insome examples, the providing a medical decision includes stratifying oneor more treatment decision options in a report based on the status ofthe one or more molecular markers. In some examples, the medicaldecision is administration of a drug. In some examples, the target isselected from the following group: diseased tissue, suspected diseasedtissue and healthy tissue. In some examples, the medical decision ischanging the dosage of a drug, selecting a frequency of drugadministration, or making a drug selection. In some examples, thedetermining a status of one or more molecular markers in a bodily fluidin the target, while simultaneously quantifying flow of the bodily fluidindicates the presence or absence of disease. In some examples, thetarget is selected from the group consisting of tissue, healthy tissue,diseased tissue, retina, tumor, cancer, growth, fibroid, lesion, skin,mucosal lining, organ, graft, blood supply and one or more bloodvessels. In some examples, determining the status of one or moremolecular markers includes imaging a blood flow or a blood supply. Insome examples, the imaging includes comparing the image of the bloodflow or the blood supply of a disease or suspected diseased tissue to animage of a blood flow or a blood supply from a normal tissue or aprevious image of a blood flow or a blood supply from the same tissue;and diagnosing the diseased tissue if the image of the blood flow or theblood supply of the suspected diseased tissue includes an increased oran abnormal levels of one or more molecular markers when compared to thelevels of molecular markers in an image of the blood flow or the bloodsupply from the normal tissue or a previous image of a blood flow or ablood supply from the same tissue.

In another aspect of the disclosure, the target is tissue suspected toinclude cancer. In some examples, cancer is selected from the groupconsisting of skin cancer, lung cancer, colon cancer, esophageal cancer,stomach cancer, ovarian cancer, thyroid cancer heart cancer, squamouscell carcinoma, fibrosarcoma, sarcoid carcinoma, melanoma, mammarycancer, lung cancer, colorectal cancer, renal cancer, osteosarcoma,cutaneous melanoma, basal cell carcinoma, pancreatic cancer, bladdercancer, liver cancer, brain cancer, prostate cancer, leukemia, melanoma,or lymphoma.

Another aspect of the disclosure provides determining a status of one ormore molecular markers is used to diagnose, monitor or treat oculardiseases selected from the group consisting of: age related maculardegeneration (AMD), wet AMD, dry AMD, glaucoma, retinal vein occlusion,branched retinal vein occlusion and diabetic retinopathy. In someexamples, determining a status of one or more molecular markers isperformed without contacting at least one analyte with an exogenousreagent or label.

Another aspect of the disclosure provides a metabolic optical coherencetomography system comprising visible light illumination and nearinfra-red illumination of a target to determine both a blood flow rateand a change in a rate of oxygen saturation.

II. General Methods for Functional OCT (fOCT) A. Terminology and OCTMethods

The terms “optical coherence tomography” and “OCT,” described herein,generally refer to an interferometric technique for imaging samples, insome examples, with micrometer lateral resolution. This non-invasiveoptical tomographic imaging technique is used in variety of medical andindustrial applications to provide cross-sectional or 3D images of atarget.

The terms “functional OCT” and “fOCT,” described herein, generally referto a method of OCT imaging that provides for the acquisition of bothstructural (3D, tomographic and cross-sectional information) andfunctional information about a target, as described herein. In someexamples, fOCT may be referred to as “visible-OCT” or “vis-OCT.” Vis-OCTgenerally refers to a type of fOCT that comprises visible light.

fOCT may utilize any method of OCT. Generally, fOCT may be configuredwith an interferometer, as is the example for many other OCT methods.Light from a light source (for example, a broadband light source) issplit (for example, by a beam-splitter) and travels along a sample arm(generally comprising the sample) and a reference arm (generallycomprising a mirror). A portion of the light from the sample armilluminates a target is reflected by the target. Light is also reflectedfrom a mirror in the reference arm. (Light from the test arm and thereference arm is recombined, for example by the beam-splitter.) When thedistance travelled by light in the sample arm is within a coherencelength of the distance travelled by light in the reference arm, opticalinterference occurs, which affects the intensity of the recombinedlight. The intensity of the combined reflected light varies depending onthe target properties. Thus, variations for the intensity of thereflectance measured are indications of the physical features orattributes of the target being imaged.

In some examples, the devices, methods and systems of the disclosure mayutilize time-domain OCT, where the length of the reference arm can bevaried (for example, by moving one or more reference mirrors). Thereflectance observed as the reference arm distance changes indicatessample properties at different depths of the sample. In some examples,the length of the sample arm is varied instead of or in addition to thevariation of the reference arm length. In some examples, the devices,methods and systems may utilize frequency-domain OCT, where the distanceof the reference arm can be fixed, and the reflectance can then bemeasured at different frequencies. For example, the frequency of lightemitted from a light source can be scanned across a range of frequenciesor a dispersive element, such as a grating, and a detector array may beused to separate and detect different wavelengths. Fourier analysis canconvert the frequency-dependent reflectance properties todistance-dependent reflectance properties, thereby indicating sampleproperties at different sample depths. In certain examples, OCT can showadditional information or data not obtainable from other forms ofimaging.

In some examples, the devices, methods and systems of the disclosure mayutilize frequency-domain optical coherence tomography, where thereference and sample arms are fixed. Light from a broadband light sourceincluding a plurality of wavelengths is reflected from the sample andinterfered with light reflected by the reference mirror/s. The opticalspectrum of the reflected signal can be obtained. For example, the lightmay be input to a spectrometer or a spectrograph, comprising, forexample, a grating and a detector array that detects the intensity oflight at different frequencies.

Fourier analysis may be performed, for example, by a processor, and mayconvert data corresponding to a plurality of frequencies to thatcorresponding to a plurality of positions within the sample. Thus, datafrom a plurality of sample depths can be simultaneously collectedwithout the need for scanning of the reference arm (or sample) arms.Additional details related to frequency domain optical coherencetomography are described in Vakhtin et al., (Vakhtin A B, Kane D J, WoodW R and Peterson K A. “Common-path interferometer for frequency-domainoptical coherence tomography,” Applied Optics. 42(34), 6953-6958 (2003))and incorporated by reference herein.

Other methods of performing optical coherence tomography are possible.For example, in some examples of frequency domain optical coherencetomography, the frequency of light emitted from a light source varies intime. Thus, differences in light intensity as a function of time relateto different light frequencies. When a spectrally time-varying lightsource is used, a detector may detect light intensity as a function oftime to obtain optical spectrum of the interference signal. The Fouriertransform of the optical spectrum may be employed as described herein.The devices, methods and systems of the disclosure may utilize anymethod of OCT, including but not limited to spectral domain OCT, Fourierdomain OCT, time encoded frequency domain OCT, or swept source OCT,single point OCT, confocal OCT, parallel OCT, or full field OCT as knownin the art.

Generally, the term “A-scan” OR “A-line” describes the lightreflectivity associated with different sample depths. The term “B-scan”or “B-line” as used herein refers to the use of cross-sectional views oftissues formed by assembly of a plurality of A-scans. In the example offOCT methods of cancer detection, light reflected by cancerous tissuetarget is converted into electrical signals and can be used to generateboth cross-sectional or 3D structural images and metabolic functionalinformation about the target tissue (such as cancerous growth, lesion,or tumor). In the example of ophthalmology, light reflected by eyetissues is converted into electrical signals and can be used to providedata regarding the 3D structure of tissue in the eye and metabolicactivity in the retina. In many examples, including but not limited tocancer detection and ophthalmology, A-scans and B-scans can be used, forexample, for differentiating normal and abnormal tissue.

For general methods, an A-scan can generally include data at pluralityof depths in a z-axis direction, and a B-scan may includecross-sectional data from a medial border to a lateral border, or (x,y)axis direction. In the example of fOCT of a skin cancer lesion, forexample, an A-scan can generally include data from the outer regions ofthe epidermis of the lesion to the inner regions comprising vasculature,while B-scans can include cross sectional data from one lesion border toanother in the (x,y) plane. In ophthalmic instances, an A-scan cangenerally include data from the cornea to the retina, and a B-scan caninclude cross-sectional data from a medial border to a lateral border ofthe eye and from the cornea to the retina. 3D C-scans may be used togenerate one or more 3D images by combining a plurality of B-scans invariety of examples.

In the present disclosure, a “target” may indicate any sample, object,or subject suitable for imaging. In some examples, a target may includebut is not limited to inanimate material such as metals, alloys,polymers, and minerals as found for industrial applications for fOCT andas described herein. In some examples, a target may be animate material,such any suitable living material including but not limited to embryos,seeds, cells, tissues, grafts, blood vessels, organs, or organisms aswould be suitable for medical and agricultural applications for fOCT asdescribed herein.

B. fOCT System Configuration

A fOCT system for data collection may be configured in a variety ofways, generally suitable with any type of OCT. FIG. 1 and FIG. 2(a)illustrate an example of data generated by an example system 200configured for metabolic imaging. The example free-space vis-OCT system200 includes lens L1 202, lens L2 204, an x-y axis linear scanningmirror unit 206 (e.g., a pair of rotatable mirrors to steer the laserbeam such as piezo-driven galvo mirrors (GM) or other rotationmechanisms such as resonance scanning mirrors, etc.), beam-splitter 208,dispersion control (DC) 210, reference mirror (REF) 212, laser 214(e.g., generated by a supercontinuum source such as a continuous wave(CW) argon-ion laser, etc.), charge-coupled device (CCD) camera 216(e.g., a two-dimensional CCD or other detector such as a CMOS camera,etc.), and computer or other processor 218.

Lenses L1 202 and L2 204 relay a beam generated by the laser 214 onto atarget pupil 220. The beam-splitter 208 works with a reference armincluding reference mirror 212 with dispersion control 210 to adjust thebeam from the laser 214. The beam is directed by the mirrors 206 throughthe lenses 202, 204 to impact the pupil 220. Resulting image informationis captured by the CCD 216 and relayed to the computer 218. The computer218 can be used to control the CCD 216 and/or other components of thesystem 200, for example.

FIG. 2(b) illustrates an example illumination spectrum obtained usingthe system 200. FIG. 2(c) shows a comparison of theoretical andexperimental axial resolutions obtained using the example system 200.

FIG. 20 provides another example of a fOCT or vis-OCT configuration. Insome examples, a supercontinuum source, 2097 is used for illumination ofa target. In some examples an open-space Michelson interferometryconfiguration may be adopted due to the minimum dispersion. The beam mayalso be collimated and split by a cube beam splitter into the referenceand sample arms. The sample arm may contain a two-dimensional galvomirror to steer the beam, and, optionally, a 0.2 magnification Kepleriantelescope to relay the beam from the galvo mirror to the target. Thereference arm may include a dispersion control glass plate, and a mirrorto illustrate the beam. The two beams from the reference and sample armsrecombined at the beam splitter and may be collected by an opticalfiber. The fiber may deliver the light to a spectrometer, which mayconsist of a collimating lens, a diffraction grating, an objective lens,and a line scan CCD camera, 2098 (e.g. Balser, sprint slp2k). The cameraexposure and the scanning galvo mirror may be synchronized by an analogoutput card.

The devices, methods, compositions, systems, and kits of the presentdisclosure may use any light source suitable for OCT, including but notlimited to supercontinuum lasers, superluminescent diodes, continuouswave lasers or ultrashort pulsed lasers. The light source may be used togenerate one or more low coherence beams of light to illuminate thetarget. In some examples, the light source may be used to generate arange of beams of light. In some examples, the light source may generatebetween 1 and 10 beams. In other examples, the light source may generatebetween 2 and 5 beams. In other examples, the light source may generatebetween 5 and 20 beams. In other examples, the light source may generatebetween 10-15 beams. In other examples, the light source may generatebetween 1 and 1000 beams of light. In other examples, the light sourcemay generate between 10 and 1000 beams of light. In other examples, thelight source may generate between 20 and 100 beams of light. In otherexamples, the light source may generate between 30 and 100 beams oflight. In other examples, the light source may generate between 40 and100 beams of light. In other examples, the light source may generatebetween 50 and 100 beams of light. In other examples, the light sourcemay generate between 60 and 1000 beams of light. In other examples, thelight source may generate between 70 and 100 beams of light. In otherexamples, the light source may generate between 1 and 80 beams of light.In other examples, the light source may generate between 90 and 100beams of light. Those of skill in the art will appreciate that thenumber of beams of light may fall within any range bounded by any ofthese values (e.g. from about 1 beam to about 1000 beams).

Generally, the wavelength range of the one or more beams of light mayrange from about 500 nm to about 620 nm. In some examples, thewavelength may range between 200 nm to 600 nm. In some examples, thewavelength may range between 300 to 900 nm. In some examples, thewavelength may range between 500 nm to 1200 nm. In some examples, thewavelength may range between 500 nm to 800 nm. In some examples, thewavelength range of the one or more beams of light may have wavelengthsat or around 500 nm, 510 nm, 520 nm, 530 nm, 540 nm, 550 nm, 560 nm, 570nm, 580 nm, 590 nm, 600 nm, 610 nm, and 620 nm. Generally, thewavelength range of the one or more beams of light may range from 200 nmto 1500 nm. In some examples, the wavelength range of the one or morebeams of light may range from 200 nm to 1500 nm. The wavelength range ofthe one or more beams of light may range from 300 nm to 1500 nm. Thewavelength range of the one or more beams of light may range from 400 nmto 1500 nm. The wavelength range of the one or more beams of light mayrange from 500 nm to 1500 nm. The wavelength range of the one or morebeams of light may range from 600 nm to 1500 nm. The wavelength range ofthe one or more beams of light may range from 700 nm to 1500 nm. Thewavelength range of the one or more beams of light may range from 800 nmto 1500 nm. The wavelength range of the one or more beams of light mayrange from 900 nm to 1500 nm. The wavelength range of the one or morebeams of light may range from 1000 nm to 1500 nm. The wavelength rangeof the one or more beams of light may range from 1100 nm to 1500 nm. Thewavelength range of the one or more beams of light may range from 1200nm to 1500 nm. The wavelength range of the one or more beams of lightmay range from 1300 nm to 1500 nm. The wavelength range of the one ormore beams of light may range from 1300 nm to 1500 nm. In some examples,fOCT and devices, methods, and systems of the present disclosure includetwo or more beams of light with wavelengths in the visible lightspectrum or the near infrared (NIR) light spectrum. In some examples,fOCT includes beams of light with wavelengths in the visible lightspectrum and the NIR spectrum. Those of skill in the art will appreciatethat the wavelength of light may fall within any range bounded by any ofthese values (e.g. from about 200 nm beam to about 1500 nm).

In some examples, fOCT may include multi-band scanning. In some examplesa band may include one or more wavelength ranges containing continuouswavelengths of light within a bounded range. In some examples a band mayinclude one or more wavelength ranges containing continuous group ofwavelengths of light with an upper limit of wavelengths and a lowerlimit of wavelengths. In some examples, the bounded ranges within a bandmay include the wavelength ranges described herein. In some examplesfOCT may include bands that overlap. In some examples, fOCT may includebands are substantially separated. In some examples, bands may partiallyoverlap. In some examples, fOCT may include one or more bands rangingfrom 1 band to 100 bands. In some the number of bands may include 1-5bands. In some the number of bands may include 5-10 bands. In some thenumber of bands may include 10-50 bands. In some the number of bands mayinclude 25-75 bands. In some the number of bands may include 25-100bands.

Generally, one or more beams of light used to illuminate a target may beconfigured in any suitable pattern. In some examples, the beams of lightmay be one or more polygon patterns. In some examples the illuminationpattern 600, (FIG. 6) may be rectangle of one or more beams, 610, 620.In some examples, the beams of light may illuminate the target as one ormore circles, (FIG. 3) or two or more concentric circles 395, with oneor more beams, 396, and 397. In some examples, a suitable pattern may bechosen based upon the pattern of vessels or fluid flow to be imaged in atarget. For example, in a retina, blood vessels are found radiallyaround the optic nerve head in a circular pattern or substantiallycircular pattern. For example, for fOCT imaging of a retina, one or moreconcentric circles of beams, or substantially circular beams, may beused to illuminate the target retina. In some examples, fOCT may beperformed with a identical or different predefined scanning trajectory.In some examples the trajectory may include a polygonal shape. In someexamples, the trajectories may be applied to a target simultaneously orsequentially.

Further, the devices, methods, and systems of the disclosure may allowfor various power requirements to generate fOCT scans as compared toother OCT or imaging methods. In some examples, an fOCT device isconfigured to illuminate a target with a light source with a range ofpower from 0.01 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source of about 0.8 mW.In some examples, a fOCT device is configured to illuminate a targetwith a light source of about 0.5 mW-0.8 mW. In some examples, a fOCTdevice is configured to illuminate a target with a light source of about0.1 mW-1.2 mW. In some examples, a fOCT device is configured toilluminate a target with a light source of about 0.2 mW-1.5 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.01 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.02 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.03 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.04 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.05 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.06 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.07 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.08 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.09 mW to 1 mW. In someexamples, a fOCT device is configured to illuminate a target with alight source with a power ranging from 0.1 mW to 1 mW. In some examples,a fOCT device is configured to illuminate a target with a light sourcewith a power ranging from 0.2 mW to 1 mW. In some examples, a fOCTdevice is configured to illuminate a target with a light source with apower ranging from 0.3 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.4 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.5 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.6 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.7 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.8 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 0.9 mW to 1 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 1.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 2.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 3.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 4.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 5.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 10.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 20.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 30.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 50.0 mW to 100 mW. In some examples, a fOCT device isconfigured to illuminate a target with a light source with a powerranging from 75.0 mW to 100 mW. Those of skill in the art willappreciate that light source power may fall within any range bounded byany of these values (e.g. from about 0.01 mW to about 100 mW).

In some examples, the devices, methods, and systems of the disclosureallow for configuration of an fOCT device to acquire A-scans at a fasterrate than other OCT or imaging methods. In some examples, A-scanacquisition rate may range from 1 kHz to 10,000 kHz. In some examples,A-scan acquisition rate may range from 5 kHz to 1000 kHz. In someexamples, A-scan acquisition rate may range from 10 kHz to 1,000 kHz. Insome examples, A-scan acquisition rate may range from 20 kHz to 1,000kHz. In some examples, A-scan acquisition rate may range from 30 kHz to1000 kHz. In some examples, A-scan acquisition rate may range from 40kHz to 1,000 kHz. In some examples, A-scan acquisition rate may rangefrom 50 kHz to 1000 kHz. In some examples, A-scan acquisition rate mayrange from 60 kHz to 1,000 kHz. In some examples, A-scan acquisitionrate may range from 70 kHz to 1000 kHz. In some examples, A-scanacquisition rate may range from 80 kHz to 1,000 kHz. In some examples,A-scan acquisition rate may range from 90 kHz to 1000 kHz. In someexamples, A-scan acquisition rate may range from 100 kHz to 1,000 kHz.In some examples, A-scan acquisition rate may range from 200 kHz to 1000kHz. In some examples, A-scan acquisition rate may range from 300 kHz to1,000 kHz. In some examples, A-scan acquisition rate may range from 400kHz to 1000 kHz. In some examples, A-scan acquisition rate may rangefrom 500 kHz to 1,000 kHz. In some examples, A-scan acquisition rate mayrange from 600 kHz to 1000 kHz. In some examples, A-scan acquisitionrate may range from 700 kHz to 1,000 kHz. In some examples, A-scanacquisition rate may range from 800 kHz to 1000 kHz. In some examples,A-scan acquisition rate may range from 900 kHz to 1,000 kHz. In someexamples, A-scan acquisition rate may range from 1000 kHz to 10000 kHz.In some examples, A-scan acquisition rate may range from about 35 kHz toabout 70 kHz. In some examples, A-scan acquisition rate may range fromabout 20 kHz to about 100 kHz. In some examples, A-scan acquisition ratemay range from about 75 kHz to about 200 kHz. In some examples, A-scanacquisition rate may range from about 100 kHz to about 500 kHz. In someexamples, A-scan acquisition rate may include a frequency of 10 kHz, 15kHz, 20 kHz, 25 kHz, 30 kHz, 35 kHz, 40 kHz, 45 kHz, 50 kHz, 60 kHz, 70kHz, 75 kHz, 80 kHz, 85 kHz, 90 kHz, or 100 kHz. Those of skill in theart will appreciate that A-scan acquisition frequency may fall withinany range bounded by any of these values (e.g. from about 1 kHz to about10000 kHz).

Each B-scan may have a plurality of A-scans, ranging from 1 to 1000. Insome examples, each B-scan may have a range of 1-10,000 A-scans. In someexamples, each B-scan may have a range of 10-1000 A-scans. In someexamples, each B-scan may have a range of 100-1000 A-scans. In someexamples, a B-can may have 256 A-scans. In some examples, each B-scanmay have a range of 200-1000 A-scans. In some examples, each B-scan mayhave a range of 300-1000 A-scans. In some examples, each B-scan may havea range of 400-1000 A-scans. In some examples, each B-scan may have arange of 500-1000 A-scans. In some examples, each B-scan may have arange of 600-1000 A-scans. In some examples, each B-scan may have arange of 700-1000 A-scans. In some examples, each B-scan may have arange of 800-1000 A-scans. In some examples, each B-scan may have arange of 900-1000 A-scans. In some examples, each B-scan may have arange of 1000-10000 A-scans. In some examples, each B-scan may have arange of 2000-10000 A-scans. In some examples, each B-scan may have arange of 3000-10000 A-scans. In some examples, each B-scan may have arange of 4000-10000 A-scans. In some examples, each B-scan may have arange of 5000-10000 A-scans. In some examples, each B-scan may have arange of 6000-10000 A-scans. In some examples, each B-scan may have arange of 7000-10000 A-scans. In some examples, each B-scan may have arange of 8000-10000 A-scans. In some examples, each B-scan may have arange of 9000-10000 A-scans. In some examples a B-scan may include 2410A-scans. In some examples a B-scan may include 2500 A-scans.

In some examples, fOCT may be performed with a range of 1-100,000,000A-scans generated for quantitatively 3D-imaging in the target. In someexamples, A-scans generated may range from 100-100,000,000. In someexamples, A-scans generated may range from 1000-100,000,000. In someexamples, A-scans generated may range from 10000-100,000,000. In someexamples, A-scans generated may range from 100000-100,000,000. In someexamples, A-scans generated may range from 1000000-100,000,000. In someexamples, A-scans generated may range from 10,000,000-100,000,000. Insome examples, about 65,000 A-scans are generated for quantitatively3D-imaging in the target. In some examples, about 50,000 A-scans aregenerated for quantitatively 3D-imaging in the target. In some examples,about 75,000 A-scans are generated for quantitatively 3D-imaging in thetarget. In some examples, about 25,000 A-scans are generated forquantitatively 3D-imaging in the target.

In some examples, an electrocardiogram (EKG) amplifier to collect an EKGsignal may be used in addition to fOCT imaging. In some examples, an EKGsignal may be useful when configuring a fOCT device for metabolicimaging of blood vessels, such as shown in FIG. 20, 2099. The EKG signalcollection may be synchronized with the scanning by an analog outputcard, so that the collections of EKG and the OCT image are simultaneous.In some examples, a pulse oximeter may also be used with fOCT, as showin FIG. 20, 2094. In some examples, a frame grabber is used with fOCT,as shown in FIG. 20, 2096. In some examples, a PC processor, 2095, ormachine can be configured with fOCT. In some examples, a PC computerprocessor may include but is not limited to a personal computer,mainframe, cell phone, mobile device, wearable device, or watch.

C. fOCT Signal Processing and Quantification

The devices, methods, and systems of the disclosure provide forquantitatively 3D-imaging in the target, a flow rate of a fluid and aconcentration of one or more analytes, from the optical informationacquired in previous steps and as described herein. In some examples,optical information is extracted from A-scans. Unlike previouslydescribed imaging methods, data sufficient for quantitatively 3D-imagingin the target, a flow rate of a fluid and a concentration of one or moreanalytes may be extracted from only optical information generated byOCT. Additionally, quantitatively 3D-imaging in the target, a flow rateof a fluid and a concentration of one or more analytes may be extractedfrom the same optical information. In some examples, the same opticalinformation may be the same A-scan. In some examples, information from asingle or same A-scan may be used to quantitatively 3D-image in atarget, a flow rate of a fluid and a concentration of one or moreanalytes. In some examples, both quantitatively 3D-imaging in thetarget, a flow rate of a fluid and a concentration of one or moreanalytes occurs simultaneously or substantially simultaneously. In someexamples, simultaneously (or substantially simultaneously given somedata transmission, storage, and/or processing latency, etc.) may referto concurrent (or substantially concurrent given some data transmission,storage, and/or processing latency, etc.) calculations. In someexamples, simultaneously may refer to both quantitatively 3D-imaging inthe target, a flow rate of a fluid and a concentration of one or moreanalytes occurring in the same system, in the same target, with the sameOCT device, or with the same algorithmic processor.

i. 3D-Imaging

FIG. 14 provides an example process scheme of methods for signalprocessing quantification for quantitatively 3D-imaging in a target, aflow rate of a fluid and a concentration of one or more analytes. Incertain examples, one or more OCT scans, 1401, are obtained. Rawspectral data is then obtained from one or more OCT scans, 1402. A-scancomplex reflectance is then obtained, 1403. From the same A-scan complexreflectance, the devices, methods and systems of the disclosure providefor calculation of flow rate of fluid in target, 1404, and calculationof one or more analyte concentration in a target, 1405. A determinationof change in target function, 1406, may be performed based on thecalculation of flow rate of fluid in target.

Before down stream quantification process elements, in some examples,one or more exposures of a CCD camera configured with the fOCT devicemay record the interferometric spectrum. In some examples, a processelement is performed before A-scans are obtained. In some examples, DCspectral background may be averaged from a portion or the entirety ofthe spectral signals. The remaining spectrum may be resampled intok-space with an equal interval. The complex reflectance signal withrespect to depth (“A-line” or “A-scan”) may be obtained by a fastFourier transform (FFT) on the k-space spectrum. The process may berepeated for all or a portion of collected A-lines described herein.Fast Fourier transforms (FFT) or any suitable methods to generate 3Dcomplex reflectance data may be used. In some examples, the amplitude ofthe complex reflectance may be used to obtain 3D morphological images.

ii. Quantifying Analyte Concentration

The devices, methods, and systems of the disclosure provide for signalprocessing that provides one or more analyte concentrations to bequantified from 3D-images generated by fOCT and as described herein.Generally, the method includes: 3D image vessel segmentation, spectralextraction, and fitting.

In some examples, vessels containing a fluid can be segmented oridentified by intensity thresholding. In some examples, vessels includebut are not limited to blood vessels. In some examples, an intensityhistogram adjustment may be performed on each B-scan image to maximizecontrast. Next, a global image threshold may be calculated using Otsu'smethods and used to binarize one or more images. In some examples, thedepth location of the first non-zero boundary from each A-scan may berecorded as the surface at that point. The same procedure may berepeated on all or a portion of the B-scans generated and describedherein.

The transverse coordinates of the vessels may then be located. A meanintensity projection from a slab around 150 to 200 f.m deep from thesurface may be taken. In some examples, a slab can range from 1 f.m to10000 f.m. In some examples, a slab can range from 100 f.m to 400 f.m.In some examples, a slab can range from 100 f.m to 900 f.m. In someexamples, a slab can range from 200 f.m to 800 f.m. In some examples, aslab can range from 300 f.m to 700 f.m. In some examples, a slab canrange from 400 f.m to 600 f.m. In some examples, a slab can range from200 f.m to 600 f.m. In some examples, a slab can range from 100 f.m to10000 f.m. In some examples, a slab can range from 200 f.m to 10000. Insome examples, a slab can range from 300 f.m to 10000. In some examples,a slab can range from 400 f.m to 10000. In some examples, a slab canrange from 500 f.m to 10000. In some examples, a slab can range from 600f.m to 10000. In some examples, a slab can range from 600 f.m to 10000.In some examples, a slab can range from 700 f.m to 10000. In someexamples, a slab can range from 800 f.m to 10000. In some examples, aslab can range from 900 f.m to 10000. In some examples, a slab can rangefrom 1000 f.m to 10000. In some examples, a slab can range from 1200 f.mto 10000. In some examples, a slab can range from 1300 f.m to 10000. Insome examples, a slab can range from 1400 f.m to 10000. In someexamples, a slab can range from 1500 f.m to 10000

Next, an adaptive thresholding procedure may be used to binarize theimage. In order to remove the noise, image dilation and erosionprocessing may be performed on the binarized image with a 3 pixel-radiandisk pattern. Each vessel may then be separated and selectedindividually. The 3D coordinates (axial and transverse) of the vesselsmay then be recorded to further extract the spectrum from these vessels.

After the 3D coordinates of each blood vessel may be determined, thecorresponding interferometric spectra may be selected from the raw dataand Short-time Fourier transform (STFT) may be performed for spectraextraction and fitting. Any suitable Gaussian window size may beapplied. In some examples, k_(w)=0.32f.m-l (17 nm at 585 nm) may be usedin the STFT. In some examples, relaxing the axial resolution to at least9 f.m. or at most 9 f.m. may be used. The spectra may then be taken fromthe bottom of a vessel wall. Various spectral fitting models are knownin the art.

Generally, an OCT signal can be modeled by different equationspertaining to an analyte. In some examples, an analyte may be oxygen,hemoglobin, deoxygenated hemoglobin or oxygenated hemoglobin. Forexample, to determine metabolic function in a retina, the followingequation may be used to model oxygen consumption:

I ² =I ₀ ² R ₀ rexp[−2ndμ _(HbO2)(sO₂)−2nd _(Hb)(1−sO₂)]

where l₀ is the incident intensity on the retina. In some examples, theoptical attenuation by ocular lens and vitreous chamber can be ignoredand thus l₀ may be considered the source spectrum; R₀ is the referencearm reflectance; d [mm] is the vessel diameter; r [dimensionless] is thereflectance at the vessel wall, whose scattering spectrum can be modeledas a power law under the first-order Born approximation r(A) AA where Ais a constant. The optical attenuation coefficient f.1 [mm⁻¹] combinesthe absorption (f.1a) and scattering coefficients (f.1s) of a fluid. Insome examples, this may be for whole blood, which may be bothwavelength- and oxygenation-dependent. In the example of oxygenated anddeoxygenated hemoglobin, the subscripts Hb and HbO₂ denote thecontribution from deoxygenated and oxygenated blood, respectively. A loglinear regression of the data may then be used on the spectra to returnthe value of sO₂. A concentration of any suitable analyte may bequantitatively obtained through 3D-imaging in the target.iii. Flow Quantification

Methods for quantifying a flow rate of fluid using OCT has beenpreviously described and are known in the art. In some examples, phasesensitive Doppler OCT may be used for flow measurement. Phase is a typeof high resolution position measurement of a reflection along theoptical path length of the imaging system, which is cyclic of thefrequency of half the wavelength of the imaging light. A depth positionchange of half the imaging wavelength will produce the same phasemeasurement. Changes in phase are proportional to the axial flow, theflow component parallel to the imaging direction designated by v(cos θ),where v is the velocity of the flow and θ is the angle between the flowdirection and the imaging light.

In phase sensitive Doppler-OCT signals from two adjacent A-lines, FIG.15, may be used to extract the velocity of a fluid, a velocity of ananalyte in the fluid or fluid viscosity. In some examples, blood flowmay be measured by determining the velocity of red blood cells. Theblood flow velocity can be expressed as:

${v = \frac{f_{sample} \cdot \lambda_{0} \cdot {\Delta\varphi}}{4 \cdot \pi \cdot n \cdot {\cos (\theta)}}},$

where f_(sample) is the OCT A-line scanning frequency; A₀ [nm] is thecenter wavelength of the light source; Δϕ is the phase shift of thecomplex reflectance between adjacent A-scans [radians]; n is therefraction index of the sample; and e [radians] is the Doppler angle;the angle between the blood vessel and probing light. The velocityprojected to the probe beam direction vp is proportional to Δϕ,

$v_{p} = \frac{{f_{sample} \cdot \lambda_{0} \cdot \Delta}\overset{.}{\varphi}}{4\pi \; n}$

the total blood flow is equal to the product of the velocity and thevessel cross sectional:

$F = {{v \times A} = {{v \times \frac{\pi \; {Dia}^{2}}{4} \times {\sin (\theta)}} = {v_{p} \times \frac{\pi \; {Dia}^{2}}{4} \times {{\tan (\theta)}.}}}}$

Thus, the post-processing for blood flow may include the followingsteps: calculation of the projected blood velocity v_(p), Doppler angleθ, and vessel diameter Dia.

The devices, methods, and systems of the disclosure provide forutilizing the same optical information used to quantify one or moreanalyte concentrations for fluid flow calculations. The opticalinformation, or in some examples, complex reflectance A-line signal fromthe Fourier transform of the interferometric spectra may be used. Insome examples, the derivative of the phase term of the complex signalbetween the adjacent A-lines may be used in quantifying fluid flow in avessel. In some examples, a median filter may be applied on one or moreB-scan phase images to remove salt and pepper noise. Δϕ is calculated bythe integration of the phase shift within each vessel lumen.

In some examples, in order to calculate the Doppler angle, dual circlescans with radius r₁ and r₂ intersect a vessel at two different vesselcenter points, S(x₁,y₁,z₁) and E(x₂,y₂,z₂). The direction of the vesselcan be expressed as a vector ES:

ES =(x ₁ −x ₂ ,y ₁ −y ₂ ,z ₁ −z ₂).

In the example of fOCT of a retina, the direction of probing light isNS′, where N is the nodal point of the eye. If the eye diameter is h,then the coordinates of N are (0,0,h) and the coordinates of S′ are(x₁′,y₁′,0). The probing light direction is:

NS ′=(x ₁ ′,y ₁ ′,−h).

The Doppler angle θ can then be calculated given the coordinates of allthe vectors:

${{\cos (\theta)} = \frac{\overset{\_}{ES} \cdot {\overset{\_}{NS}}^{\prime}}{\left| \overset{\_}{ES} \middle| {\cdot \left| {\overset{\_}{NS}}^{\prime} \right|} \right.}},$

where r₁ and r₂ are the radii of the outer and inner circular scans onretina respectively, and <1 and <2 are the azimuthal angles of thecircular scans. The z coordinates may be measured directly from theB-scan OCT images. Considering the retina is thin (200f.m) compared tothe eyeball diameter (h=6 mm for rats), the coordinates of E′ and S′ canbe expressed as:

x ₁ =r ₁×cos(φ₁)

x ₂ =r ₂×cos(φ₂)

y ₁ =r ₁×sin(φ₁)

y ₂ =r ₂×sin(φ₂).

In some examples, circular B-scan images from <=0 to 360 degreehorizontally may be used. The vertical axis z is the depth, where thelow boundary of B-scan image was set as z=0. Vessels can be segmentedfrom the outer and inner scanning circular B-scan images. The zcoordinates as well as r_(p1) and r_(p2) could be measured. r₁ and r₂can be calculated by:

r ₁ =h·tan(ϕ₁),r ₂ =h·tan(ϕ₂).

The scanning angles ϕ₁ and ϕ₂ may be set as 4 degree and 6 degree by thegalvo mirrors, respectively. Given all the coordinates, the Dopplerangle θ could be calculated according to:

${\cos (\theta)} = {\frac{\overset{\_}{ES} \cdot {\overset{\_}{NS}}^{\prime}}{\left| \overset{\_}{ES} \middle| {\cdot \left| {\overset{\_}{NS}}^{\prime} \right|} \right.}.}$

In order to calculate flow, the cross sectional diameter and area mayalso be used. Vessel height H may be obtained axially from amplitudeB-scan image. The diameter of the blood vessel Dia may then be equal to:

Dia=H×sin(θ)

and Dia can be solved.

Analytes as described herein may refer to any chemical or biochemicalmoiety suitable for imaging. In some examples, this may include but isnot limited to oxygen, hemoglobin, oxygenated hemoglobin, deoxygenatedhemoglobin, glucose, sugar, blood area nitrogen, lactate, hematocrit,biomarker, molecular marker, or nucleic acid that maybe suitable toimage to determine target function. The analytes may also be molecules,including but not limited to: polypeptides, proteins, antibodies,enzymes, nucleic acids, saccharides, small molecules, drugs, and thelike.

In some examples, the devices, methods, and systems of the disclosureprovide for “label-free” quantitatively 3D-imaging in the target, a flowrate of a fluid and a concentration of one or more analytes. In thisexample, analytes and flow are calculated without the use of exogenousreagents contacted with either the analytes or the targets. For example,a variety of imaging methods have been described describing quantifyinganalytes or flow with the use of contrast reagents or additionalchemical markers or signals that may bind to one more analytes. Thedevices, methods, and systems of the disclosure provide an imagingsystem where one or more analytes imaged are label-free.

In some examples, however, one or more contrast reagents may be used inconjunction with the devices, methods, and systems of the disclosure. Inthis example, quantitatively 3D-imaging in the target, a flow rate of afluid and a concentration of one analyte may be obtained without alabel, while one more additional analyte concentrations may bedetermined by contacting one or more analytes with a exogenous reagentsuch as contrast reagent.

A target may include any vessel or structure that can contain a fluid tobe imaged including but not limited to tissue, healthy tissue, diseasedtissue, retina, tumor, cancer, growth, fibroid, lesion, skin, mucosallining, organ, graft, blood supply and one or more blood vessels.

In some examples, a fluid may include but is not limited to whole blood,blood plasma, blood serum, urine, semen, tears, sweat, saliva, lymphfluid, pleural effusion, peritoneal fluid, meningal fluid, amnioticfluid, glandular fluid, spinal fluid, conjunctival fluid, vitreous,aqueous, vaginal fluid, bile, mucus, sputum and cerebrospinal fluid.

iv. Determining a Rate of Change of Analyte and Target Function

Generally, the devices, methods, and systems of the disclosure provideprocesses to determine the rate of change of concentration of analyte.Quantitatively imaging a flow rate of a fluid in the target and aconcentration of one or more analytes in the fluid in the target may beperformed at one time point or over a succession of time points. In someexamples, a target may be monitored over a period of time of at least 1msec, 1 sec, 1 min, 1 hr, 1 day, 1 week, 1 month, 1 year, and 10 years.In some examples, a target may be monitored over period of time of atmost 1 msec, 1 sec, 1 min, 1 hr, 1 day, 1 week, 1 month, 1 year, and 10years. In some examples, a target may be monitored for 20-60 min. Insome examples, a target may be monitored over 1 to 5 years. In someexamples, a target may be monitored for 1 to 60 secs. In some examples,a target may be monitored for 1 ms to 500 msec.

In some examples, target function may include but is not limited tometabolic activity, metabolic rate, oxygen consumption, tissueconsumption of a biomarker or analyte, pathophysiological alterations,pathological alterations, histological change such as tissue remodeling,abnormal growth of one or more blood vessels, or abnormal tissue growth,necrosis, apoptosis, necrosis, angiogenesis, cell proliferation,neurmodulation, neural activity, wound healing, infection, burns,scarring, radiological damage, hypoxia, oxidative stress and the like.

In some examples, a change in target function may be determined bycomparing information from 3D-imaging in the target, a flow rate of afluid and a concentration of one or more analytes to a reference. Insome examples a reference many include but is not limited to a healthyimage, or an average of information from healthy subjects. In someexamples, a reference may include information from a 3D-image generatedat a different time. In some examples one or more references may becompared to other references to determine a change in rate of one ormore analyte concentrations.

III. Functional OCT and Metabolic Activity

In some examples, fOCT may be used specifically for metabolic imaging ofone or more tissues. In certain examples, metabolic imaging may providediagnostic information regarding the health status of a tissue in asubject.

Using the example system 200 of FIG. 2(a), visible-light opticalcoherence tomography (vis-OCT) can quantify rMRO2 in vivo through theconcurrent measurement of the blood flow and sO2 from retinalcirculation. Using an OCT spectral analysis, sO2 can be measured invivo. 3D imaging capability allows vis-OCT to recover optical spectraspecifically from blood vessels and eliminate a confounding signal fromother retinal layers. Metabolic rate rMRO2 may be obtained by combiningthe sO2 measurement with the OCT flow measurement.

In operation, for example, the three-dimensional (3D) structure of aretina may be scanned by passing a focused broadband laser across theretina to provide transverse (x,y) discrimination. A reflectance atdepth (z), A-line, is reconstructed based on interference betweenreflected light and a reference light.

Each 3D measurement (e.g., 2.8 mm by 2.8 mm by 1 mm in x, y, z) may takeonly several seconds (e.g., 2.5 s) with a high frame rate (e.g., 98fps), allowing monitoring of the rMRO2 with high temporal resolution. Toquantify the rMRO2 (e.g., gas volume of oxygen consumed per unit time,mL/min), two parameters are measured from the retinal circulation: totalretinal blood flow F [J·L/min] and relative sO2 [percent]. The rMRO2 canbe calculated according to the following equation:

rMRO ₂=1.34×C _(H) _(b) ×F×(s _(a)O₂ −s _(v)O₂),

where C_(Hb) is a hemoglobin concentration [g/J·L], and 1.34 is anoxygen-binding capacity of hemoglobin [mL/g]. The subscript of w and vdenotes arterial and venous sO2. Blood flow is a product ofcross-sectional vessel area (s) and velocity (v), where s is calculatedfrom a tomographic image and v is measured based on the phase variationfrom the moving blood cells. The contrast for sO2 is from the distinctabsorption spectra for oxy- and deoxyhemoglobin, for example. By fittingthe blood spectra extracted from blood vessels, a percentage ofoxyhemoglobin in total hemoglobin (sO2 by definition) can be calculated,for example.

In operation, certain examples provide a dual-beam scanning method toachieve metabolic imaging. A first beam is generated usingvisible-light, and a second beam is generated using NIR light. Thevisible-light OCT beam measures sO₂, and the NIR-light OCT beam measuresblood flow. The dual-beam OCT system and associated scanning patternscan be designed in multiple ways. FIG. 2(a) provides one example system200 able to generate and measure a variety of beam patterns andresulting illumination. For example, FIG. 3 shows a circular dual-beamscanning method 395. As shown in the example of FIG. 3, a first beam 396is a visible light beam to measure sO₂ in a target pupil, and a secondbeam 397 is a near-infrared beam to measure blood flow in the pupil.Using the dual-beam circular scanning method, beams 396, 397 move in acircular motion around an optic nerve head (ONH). Because retinal bloodvessels run radially from the ONH, each circle of the beams crossed allof the arteries and veins attached to the retina and allow capture oftotal retinal blood flow. The displacement of vessels between the twocircular scans also provides vessel directionality for absolute flow.High-speed scanning also facilitates capture of a pulsatile profile ofthe blood flow, for example.

FIG. 4 illustrates an alternative dual-beam circular scanning system 400designed with one OCT as an open-space based system and another OCT as afiber-optics based system. The example system 400 includes a computer orother processor 401 controlling two spectrometers 402, 404 to analyzeillumination generated by a super continuum laser 406. The laser 406uses a filter 408, which separates the laser light into visible 410 andNIR 412 wavelengths.

Visible light beam 410 is directed through a beamsplitter 415 andregulated with a DC 413, an iris 414, and a mirror 416 to be illustratedfrom a hot mirror (HM) 418 to an XY scan mirror 420 and onto a targeteye 440. The NIR beam 412 passes through fiber-optics 422 and isregulated using a combination of a polarization control (PC) 424, a DC426, an iris 428, and a mirror 430. The NIR beam 412 is illustrated byan XY scan mirror 432 to the HM 418 and then onto the target eye 440 viathe XY scan mirror 420.

FIG. 5 illustrates an alternative dual-beam circular scanning system 500designed with two OCTs optical fiber based systems. The example system500 includes a computer or other processor 501 controlling twospectrometers 502, 504 to analyze illumination generated by a supercontinuum laser 506. The laser 506 uses a filter 508, which separatesthe laser light into visible 510 and NIR 512 wavelengths.

Visible light beam 510 is directed through fiber optics 514 to an HM516. The visible light 510 is regulated with a PC 518, a DC 520, an iris522, and a mirror 524. The visible light 510 is steered from the HM 516to an XY scan mirror 526 and onto a target 540. The NIR beam 512 passesthrough fiber-optics 528 and is regulated using a combination of apolarization control (PC) 530, a DC 532, an iris 534, and a mirror 536.The NIR beam 512 is reflected by an XY scan mirror 538 to the HM 516 andthen onto the target 540 via the XY scan mirror 526.

While example systems 500 and 600 achieve the same purpose of metabolicOCT, the systems 500, 600 achieve that result with a different vis-OCTdesign. The dual fiber-optic OCT based system 600 can be more compactthan the system 500, but data processing is equivalent between theoutputs of the two systems 500, 600. Any of systems 200, 500, 600 can beused to implement various beam patterns, although system 200 is bettersuited for circular beam pattern 300.

FIG. 6 illustrates an alternative dual-beam linear scanning method 600.As demonstrated in the example of FIG. 6, a first beam 610 is a visiblelight beam to measure s02 in a target pupil, and a second beam 620 is anear-infrared beam to measure blood flow in the pupil. Each beam 610,620 moves along a separate path to scan a portion of retinal bloodvessels. Any of the example systems 200, 400, 500 can be used to executethe distinctive paths dual beam method 600.

FIG. 7 illustrates an alternative dual-beam linear scanning method 700.As demonstrated in the example of FIG. 7, a first beam 710 is a visiblelight beam to measure s02 in a target pupil, and a second beam 720 is anear-infrared beam to measure blood flow in the pupil. In the examplemethod 700, beams 710 and 720 moves along a same path, separated by adetermined distance, to scan a portion of retinal blood vessels. Any ofthe example systems 200, 400, 500 can be used to execute the spatialseparation dual beam method 700.

FIG. 8 illustrates an alternative dual-beam circular scanning system800. The dual-beam circular scanning system 800 includes one OCT as anopen-space based system and another OCT as a fiber-optics based systemand represents a variation in the design of system 400. Specifically,rather than using an HM 412 and a second XY scanning unit 432, theexample system 800 uses only one XY scanning unit 820 and instead uses awedge prism 850 and a third mirror 852 to steer visible 810 and NIRbeams 812 to a target 840 via the XY scan unit 820.

FIG. 9 illustrates an example dual-beam circular scanning system 900.The dual-beam circular scanning system 900 includes two optical fiberbased OCTs and represents a variation in the design of system 500.Specifically, rather than using an HM 516 and a second XY scanning unit538, the example system 800 uses only one XY scanning unit 920 andinstead uses a wedge prism 950 and a third mirror 952 to steer visible910 and NIR beams 912 to a target 940 via the XY scan unit 920.

FIGS. 10(a)-(d) show example sO₂ information acquired noninvasively froma subject's eye using visible-light OCT. FIG. 10(a) displays a fundusimage in grayscale in inversed contrast. The bright blood vesselstructure corresponds to the strong optical attenuation in blood.

For comparison, the 3D OCT volume was sectioned and used to project amean intensity. FIG. 10(b) illustrates a resulting enhanced contrastfrom the microvasculature of the eye. Also, mean sO2 values in majorvessels can be quantified, resulting in a sO2 pseudo-color map overlayshown in FIG. 10(b).

In the example of FIG. 10(a), a circular scanning pattern was employedaround the optic disk (e.g., with 4096 A-lines) to sample all majorblood vessels in the eye. FIG. 10(c) shows the circular scan of FIG.10(a) expanded into a B-scan image, where a vessel index corresponds toa number on the circle scan in FIG. 10(a). The values of sO2 inindividual vessels are shown in FIG. 10(d). In a color image, red andblue color could label arteries and veins, respectively.

FIGS. 11(a)-(g) show example blood velocity and flow measurementinformation obtained through dual-scan NIR light OCT. FIG. 11(a) showsan example retinal fundus image of spectral domain optical coherencetomography (SD-OCT). White rings indicate locations at which dual beamlaser scans were performed, each pair including one big circle and onesmall circle scan. FIG. 11(b) shows a sample amplitude SDOCT image. FIG.11(c) depicts a corresponding phase SD-OCT image of FIG. 11(b).

FIG. 11(d) represents Doppler angles for blood vessels. The upperportion of FIG. 11(d) shows a Doppler angle of one sample vessel(indicated within a black dashed square in FIG. 11(c)). The lowerportion of FIG. 11(d) provides statistic results of Doppler anglesacross 8 pairs of data.

FIG. 11(e) provides an analysis of blood velocity within the samplevessel (e.g., within the black dashed square in FIG. 11(c). The upperportion of FIG. 11(e) shows a velocity distribution of the whole samplevessel. The lower portion of FIG. 11(e) shows a transversal velocitydistribution in a direction indicated by the dashed line in FIG. 11(e).In the example of FIG. 11(e), raw data is fitted by quadratic function.

FIG. 11(f) illustrates example statistical results of blood velocity for12 retinal vessels across 8 pairs of data. FIG. 11(g) shows examplestatistical results for blood flow in retinal veins and arteries across8 pairs of data. In the example of FIG. 11(g) each bar is 200 um.

Thus, certain examples provide in vivo retinal oximetry by vis-OCT basedon a comprehensive analytical model describing both scattering andabsorption from whole blood, as well as blood vessel scattering. Oxygenconsumption is based on blood flow rate and a change in oxygensaturation rate (sO2) based on simultaneous scanning with both visibleand NIR light. Retinal metabolic rate can then be derived. Certainexamples provide parameter measurement, rather than estimation. Certainexamples provide total blood flow and/or regional blood flow in bloodvessels associated with a target retina.

Microvasculature visualization 1322 may also be determined based on thevolumetric data set and the surface topography previously computed. Aslab is sliced from the 3D volumetric dataset (e.g., 150 to 200!Jm deepfrom retinal surface), and a 2D mean intensity projection map is createdfrom the slab. Next, morphological closing is performed with a radialdisk pattern (e.g., 3 pixel) to obtain an inhomogeneous intensitybackground. Then, the 2D mean intensity projection map is normalized bythis background to enhance the contrast from the microvasculature.

IV. Medical Applications

In various examples, one or more fOCT images may provide data from whicha diagnosis and/or evaluation may be made. In some examples, suchdeterminations may relate to biologic tissue structure, vasculature,and/or microcirculation. For example, in some examples, 3-D in vivoimaging of a biologic tissue and quantifying flow of blood throughindividual vessels therein may be useful in understanding mechanismsbehind a number of disease developments and treatments including, forexample, ischemia, degeneration, trauma, seizures, and various otherneurological diseases. In still other examples, an OCT image andtechniques herein disclosed may be used to identify cancer, tumors,dementia, and ophthalmologic diseases/conditions (including, e.g.,glaucoma, diabetic retinopathy, age-related macular degeneration). Stillfurther, in various examples, OCT techniques as herein disclosed may beused for endoscopic imaging or other internal medicine applications. Insome examples, fOCT may be used to stratify treatment options, such aspersonalizing or tailoring a patient treatment specific treatmentprotocol. In some examples, fOCT may be used as a companion diagnosticfor one or more drugs. In some examples, fOCT may also be used to assessefficacy of a drug treatment during monitoring of a disease. In someexamples, fOCT may also be used to screen drug efficacy during drugdevelopment. The foregoing illustrative examples of diagnosis and/orevaluation are exemplary and thus examples of the present invention arenot limited to the examples discussed.

A. fOCT and Medical Decisions

In some examples, fOCT may be used to provide a medical decision. Insome examples, a medical decision may include but is not limited to atreatment step, diagnostics, monitoring, follow-up, evaluation,confirmation of a diagnosis, prognosis, selecting a drug for a patient,changing a drug treatment to another drug, stopping a drug treatment,changing a treatment or drug dosage, increasing or decreasing frequencyof treatment or drug administration, or recommending further evaluation.In some examples, a medical decision may be the guidance of a surgicaltool or a surgical operation. In some examples, a medical decision maybe the placement of one or more medical instruments or tools, such asthe placement of a stent, or the placement of a suture. In someexamples, a medical decision may be the determining of surgical marginsin the excision of a tumor.

B. Molecular Markers, Contrast Reagents and Bodily Fluids

In some examples fOCT may be used to detect or quantify a variety ofmolecular markers, which may be associated with a disease. The termmolecular marker as defined herein includes, but is not limited to, amolecule or biomolecule, a whole cell or a commercially importantsubstrate that may need to be tracked for its distribution oridentification. Molecules and biomolecules include nucleic acids,peptides, proteins, oligosaccharides, lipids, antigens, and smallmolecules. Commercially important substrates include, but are notlimited to, organic and inorganic polymers, small molecules or chemicalmoieties or products made therefrom. In some examples, the molecularmarker may include but is not limited to oxygen, hemoglobin, oxygenatedhemoglobin, deoxygenated hemoglobin, glucose, sugar, blood areanitrogen, lactate, hematocrit, biomarker and nucleic acid.

In some examples, one or more contrast reagents may be used incombination with the devices, methods and systems of the presentdisclosure. Generally, the disclosure provides for the quantification ofa flow rate of a fluid and concentration of one or more analytes intarget, where at least one of the analytes is not contacted with anexogenous reagent. In other examples, a contrast reagent or label may beincluded to quantify one or more analytes in addition to, or incombination with the quantification of a flow rate of a fluid andconcentration of one or more analytes that have not been contacted witha contrast reagent or label.

It is known the art, that numerous types of contrast reagents and labelsmay be used for the detection and quantification of different analytes.In some examples, contrast reagents, exogenous reagents may be anysuitable chemical, moiety or molecule that may provide a spectral signalto allow the analyte or flow rate to be scanned and quantified by OCT.In some examples, a contrast reagent or label may include a chemicallylinked moiety, ligand, antibody, small molecule, organic molecule,radioactive probe, nucleic acid and the like.

In some examples, the concentration of one or more molecular markers maybe determined in one or more bodily fluids. Generally, any bodily fluidmay be suitable for imaging with fOCT. In some examples, a bodily fluidmay include but is not limited to whole blood, blood plasma, bloodserum, urine, semen, tears, sweat, saliva, lymph fluid, pleuraleffusion, peritoneal fluid, meningal fluid, amniotic fluid, glandularfluid, spinal fluid, conjunctival fluid, vitreous, aqueous, vaginalfluid, bile, mucus, sputum and cerebrospinal fluid.

C. Stratification of Treatment Decisions

The methods of the provided disclosure can include using the status ofone or more molecular markers determined in a target to stratify (rank)treatment options for a subject. In some examples, treatment may includeany medical decisions as described herein. In some examples, one or moredrugs may be stratified based on information determined by fOCT. Thestratifying of drug treatments can be based on scientific informationregarding the molecular markers. For example, the scientific informationcan be data from one or more studies published in one or more scientificjournals (e.g., New England Journal of Medicine (NEJM), Lancet, etc.).The scientific information can be data provided in a commercial database(e.g., data stored in a database provided by Ingenuity® Systems). One ormore pieces of scientific information can be used to stratify thetreatments. In some examples, the data or scientific information may notbe published. In some examples the data or scientific information ismaintained in a private database and used for comparison across selectpatients or sub groups of patients.

i. Classes of Drugs

Drug treatment options can be stratified into classes based on thestatus of one or more molecular markers in a target. For example, afirst class of drug treatment options can be those for which scientificinformation predicts a drug will be efficacious for a subject whosetarget has one or more molecular markers of a particular status. Drugsin this first class can be a recommended drug treatment option for asubject.

A second class of drug treatment options can be those for which somescientific information predicts a drug will be efficacious for a subjectwith one or more molecular markers of a particular status, and somescientific information does not support use of the drug for the subject,based on one or more molecular markers of a particular status in asample from a subject. For example, a sample may contain a marker whosestatus indicates the drug will be efficacious in the subject and anothermarker (e.g., a particular metabolic profile that indicates a specificdisease state or stage) or may indicate the drug would also have a toxicaffect on the subject.

This second class can also include drugs for which there is indirectscientific support for drug efficacy in a subject (e.g., the drugtargets a protein that is in the same molecular pathway as a molecularmarker in a target). For example, a drug in this class could target akinase that functions downstream of an overexpressed variant of VEGF,which correlates with higher metabolic rate in a target as determined byfOCT. A drug in this second class can be a recommended drug treatmentoption for a subject.

A third class of drugs can be those for which scientific informationindicates the drug will not be efficacious in the subject based on thestatus of one or more molecular markers in a sample from the subject.For example, a drug that targets a cell surface receptor may not displayefficacy if information provided by fOCT imaging does not correlate wellif efficacy. It can be recommended that a subject not be treated with adrug in this third class.

The drug treatment options can be stratified using an algorithm-basedapproach. The status of one or more molecular markers in a patientsample is determined. The scientific literature or a database of curatedfOCT scans of one or more similar targets of one or more subjects isanalyzed for information related to the status of the molecular markerand the efficacy of one or more different drugs. If the status of amolecular marker correlates with efficacy of a drug, then arecommendation can be made to treat the subject with that drug. If thestatus of a molecular marker does not correlate with efficacy of a drug,then a recommendation can be made not to treat a subject with the drug.A computer and computer readable medium can be used to stratify the drugtreatment options.

A list of stratified drug treatment options can be presented in the formof a report. The stratification of drug treatment options can beindicated by color coding. For example, drugs in the first class can becolor coded in green, drugs in the second class can be color coded inyellow, and drugs in the third class can be color coded in red.

The recommendation of a drug treatment option for a subject can be basedon the stage of the diseases, (e.g. cancer of the subject, e.g., a latestage cancer, AMD, late stage AMD). Drug treatment options can also bestratified based on other factors, e.g., the type of disease, age of thesubject, status of drug metabolism genes (genes involved in absorption,distribution, metabolism, and excretion), efficacy of other drugs thepatient has received, clinical information regarding the subject, andfamily medical history.

In some examples, particular classes of drugs may be useful fortreatment. In some examples, when fOCT is used to determine metabolicrate of tissues as result of abnormal blood vessel proliferation ordecrease, drugs known to affect blood vasculature may be suitable. Insome examples this may include but is not limited to an angiogenesisinhibitor, e.g., a VEGF (Vascular Endothelial Growth Factor) pathwayinhibitor, e.g., a VEGF pathway inhibitor described herein, e.g., a VEGFinhibitor, e.g., a small molecule inhibitor, protein, e.g., a fusionprotein (e.g., aflibercept) or an antibody against VEGF, e.g.,bevacizumab; or a VEGF receptor inhibitor (e.g., a VEGF receptor 1inhibitor or a VEGF receptor 2 inhibitor), e.g., a small moleculeinhibitor, e.g., sorafenib, sunitinib, pazopanib or brivanib, or anantibody against VEGF receptor.

B. Diseases

fOCT may be used in medical decisions related to a variety of diseases.These may include neurological diseases, which may include but is notlimited to dementia, concussion, Alzheimer's disease, Parkinson'sdisease, peripheral neuropathy, epilepsy and multiple sclerosis. In someexamples, these may include vascular diseases, including but not limitedto diabetes, peripheral vascular diseases, stroke, cardiovasculardiseases, myocardial infarction, and aneurysm.

In some examples, fOCT may be used to provide medical decision forocular diseases which may include but is not limited to autosomalretinitis pigmentosa, autosomal dominant retinitis punctual albescens,butterfly-shaped pigment dystrophy of the fovea, adult vitelliformmacular dystrophy, Norrie's disease, blue cone monochromasy,choroideremia, gyrate atrophy, age-related macular degeneration,retinoblastoma, anterior and posterior uveitis, retinovascular diseases,cataracts, corneal dystrophies, retinal detachment, degeneration andatrophy of the iris, and diabetic retinopathy, herpes simplex virusinfection, cytomegalovirus, allergic conjunctivitis, dry eye, lysosomalstorage diseases, glycogen storage diseases, disorders of collagen,disorders of glycosaminoglycans and proteoglycans, sphinogolipodoses,mucolipidoses, disorders of amino acid metabolism, dysthyroid eyediseases, anterior and posterior corneal dystrophies, retinalphotoreceptor disorders, corneal ulceration, and ocular wounds.

In some examples fOCT may be used for medical decisions related tocancer, for example, acute myeloid leukemia; bladder cancer, includingupper tract tumors and urothelial carcinoma of the prostate; bonecancer, including chondrosarcoma, Ewing's sarcoma, and osteosarcoma;breast cancer, including noninvasive, invasive, phyllodes tumor, Paget'sdisease, and breast cancer during pregnancy; central nervous systemcancers, adult low-grade infiltrative supratentorialastrocytoma/oligodendroglioma, adult intracranial ependymoma, anaplasticastrocytoma/anaplastic oligodendroglioma/glioblastoma multiforme,limited (1-3) metastatic lesions, multiple (>3) metastatic lesions,carcinomatous lymphomatous meningitis, nonimmunosuppressed primary CNSlymphoma, and metastatic spine tumors; cervical cancer; chronicmyelogenous leukemia (CML); colon cancer, rectal cancer, anal carcinoma;esophageal cancer; gastric (stomach) cancer; head and neck cancers,including ethmoid sinus tumors, maxillary sinus tumors, salivary glandtumors, cancer of the lip, cancer of the oral cavity, cancer of theoropharynx, cancer of the hypopharynx, occult primary, cancer of theglottic larynx, cancer of the supraglottic larynx, cancer of thenasopharynx, and advanced head and neck cancer; hepatobiliary cancers,including hepatocellular carcinoma, gallbladder cancer, intrahepaticcholangiocarcinoma, and extrahepatic cholangiocarcinoma; Hodgkindisease/lymphoma; kidney cancer; melanoma; multiple myeloma, systemiclight chain amyloidosis, Waldenstrom's macroglobulinemia;myelodysplastic syndromes; neuroendocrine tumors, including multipleendocrine neoplasia, type 1, multiple endocrine neoplasia, type 2,carcinoid tumors, islet cell tumors, pheochromocytoma, poorlydifferentiated/small cell/atypical lung carcinoids; Non-Hodgkin'sLymphomas, including chronic lymphocytic leukemia/small lymphocyticlymphoma, follicular lymphoma, marginal zone lymphoma, mantle celllymphoma, diffuse large B-Cell lymphoma, Burkitt's lymphoma,lymphoblastic lymphoma, AIDS-Related B-Cell lymphoma, peripheral T-Celllymphoma, and mycosis fungoides/Sezary Syndrome; non-melanoma skincancers, including basal and squamous cell skin cancers,dermatofibrosarcoma protuberans, Merkel cell carcinoma; non-small celllung cancer (NSCLC), including thymic malignancies; occult primary;ovarian cancer, including epithelial ovarian cancer, borderlineepithelial ovarian cancer (Low Malignant Potential), and less commonovarian histologies; pancreatic adenocarcinoma; prostate cancer; smallcell lung cancer and lung neuroendocrine tumors; soft tissue sarcoma,including soft-tissue extremity, retroperitoneal, intra-abdominalsarcoma, and desmoid; testicular cancer; thymic malignancies, includingthyroid carcinoma, nodule evaluation, papillary carcinoma, follicularcarcinoma, Hurthle cell neoplasm, medullary carcinoma, and anaplasticcarcinoma; uterine neoplasms, including endometrial cancer and uterinesarcoma.

Methods for Drug Screening and Development

The devices, methods, and systems of the disclosure provided can alsoinclude means for investigating the efficacy of drugs on sample or testsubject. Generally, devices and methods of fOCT may be used for platformscreening of drugs, which may include either biologics or smallmolecule. In some examples, fOCT may be useful in determining theefficacy of a potential drug target which may be designed to increase ordecrease a particular molecular maker or analyte in a target. Forexample, if a VEGF inhibitor is screened for use in the retina, fOCT maybe used to assess candidate molecules for potential efficacy, toxicityand dosing.

In some examples, a sample may include an in vitro cultured tissuegraft, a harvested graft (e.g. from a cadaver, or an artificially growntissue. In some examples, a test subject may include an animal, orgenetically modified organism. In some examples, the geneticallymodified organism may be exhibit one or more disease states or symptomsfor which drug efficacy is tested. The provided method can also includehigh-throughput screening of FDA approved off-label drugs, experimentaldrugs, treatment protocols or pharmaceutical reagents.

V. Software and Computer Systems for fOCT

In various examples, certain methods and systems may further includesoftware programs on computer systems and use thereof. Accordingly,computerized control for the synchronization of system functions such aslaser system operation, fluid control function, and/or data acquisitionsteps are within the bounds of the invention. The computer systems maybe programmed to control the timing and coordination of delivery ofsample to a detection system, and to control mechanisms for divertingselected samples into a different flow path. In some examples of theinvention, the computer may also be programmed to store the datareceived from a detection system and/or process the data for subsequentanalysis and display.

The computer system 2500 illustrated in FIG. 25 may be understood as alogical apparatus that can read instructions from media 2511 and/or anetwork port 2505, which can optionally be connected to server 2509having fixed media 2512. The system, such as shown in FIG. 25 caninclude a CPU 2501, disk drives 2503, optional input devices such askeyboard 2515 and/or mouse 2516 and optional monitor 2507. Datacommunication can be achieved through the indicated communication mediumto a server at a local or a remote location. The communication mediumcan include any means of transmitting and/or receiving data. Forexample, the communication medium can be a network connection, awireless connection or an internet connection. Such a connection canprovide for communication over the World Wide Web. It is envisioned thatdata relating to the present disclosure can be transmitted over suchnetworks or connections for reception and/or review by a party 2522 asillustrated in FIG. 25.

FIG. 29 is a block diagram illustrating a first example architecture ofa computer system 100 that can be used in connection with exampleexamples of the present invention. As depicted in FIG. 29, the examplecomputer system can include a processor 102 for processing instructions.Non-limiting examples of processors include: Intel Xeon™ processor, AMDOpteron™ processor, Samsung 32-bit RISC ARM 1176JZ(F)-S vl .O™processor, ARM Cortex-A8 Samsung S5PC100™ processor, ARM Cortex-A8 AppleA4™ processor, Marvell PXA 930™ processor, or a functionally-equivalentprocessor. Multiple threads of execution can be used for parallelprocessing. In some examples, multiple processors or processors withmultiple cores can also be used, whether in a single computer system, ina cluster, or distributed across systems over a network comprising aplurality of computers, cell phones, and/or personal data assistantdevices.

As illustrated in FIG. 29, a high speed cache 104 can be connected to,or incorporated in, the processor 102 to provide a high speed memory forinstructions or data that have been recently, or are frequently, used byprocessor 102. The processor 102 is connected to a north bridge 106 by aprocessor bus 108. The north bridge 106 is connected to random accessmemory (RAM) 110 by a memory bus 112 and manages access to the RAM 110by the processor 102. The north bridge 106 is also connected to a southbridge 114 by a chipset bus 116. The south bridge 114 is, in turn,connected to a peripheral bus 118. The peripheral bus can be, forexample, PCI, PCI-X, PCI Express, or other peripheral bus. The northbridge and south bridge are often referred to as a processor chipset andmanage data transfer between the processor, RAM, and peripheralcomponents on the peripheral bus 118. In some alternative architectures,the functionality of the north bridge can be incorporated into theprocessor instead of using a separate north bridge chip.

In some examples, system 100 can include an accelerator card 122attached to the peripheral bus 118. The accelerator can include fieldprogrammable gate arrays (FPGAs) or other hardware for acceleratingcertain processing. For example, an accelerator can be used for adaptivedata restructuring or to evaluate algebraic expressions used in extendedset processing.

Software and data are stored in external storage 124 and can be loadedinto RAM 2910 and/or cache 104 for use by the processor. The system 100includes an operating system for managing system resources; non-limitingexamples of operating systems include: Linux, Windows™, MACOS™,BlackBerry OS™, iOS™, and other functionally-equivalent operatingsystems, as well as application software running on top of the operatingsystem for managing data storage and optimization in accordance withexample examples of the presently disclosed technology.

In this example, system 100 also includes network interface cards (NICs)120 and 121 connected to the peripheral bus for providing networkinterfaces to external storage, such as Network Attached Storage (NAS)and other computer systems that can be used for distributed parallelprocessing.

FIG. 30 is a diagram showing a network 3000 with a plurality of computersystems 3002 a, and 3002 b, a plurality of cell phones and personal dataassistants 3002 c, and Network Attached Storage (NAS) 3004 a, and 3004b. In example examples, systems 3002 a, 3002 b, and 3002 c can managedata storage and optimize data access for data stored in NetworkAttached Storage (NAS) 3004 a and 3004 b. A mathematical model can beused for the data and be evaluated using distributed parallel processingacross computer systems 3002 a, and 3002 b, and cell phone and personaldata assistant systems 3002 c. Computer systems 3002 a, and 3002 b, andcell phone and personal data assistant systems 3002 c can also provideparallel processing for adaptive data restructuring of the data storedin Network Attached Storage (NAS) 3004 a and 3004 b. FIG. 30 illustratesan example only, and a wide variety of other computer architectures andsystems can be used in conjunction with the various examples of thepresently disclosed technology. For example, a blade server can be usedto provide parallel processing. Processor blades can be connectedthrough a back plane to provide parallel processing. Storage can also beconnected to the back plane or as Network Attached Storage (NAS) througha separate network interface.

In some example examples, processors can maintain separate memory spacesand transmit data through network interfaces, back plane or otherconnectors for parallel processing by other processors. In otherexamples, some or all of the processors can use a shared virtual addressmemory space.

FIG. 31 is a block diagram of a multiprocessor computer system 302 usinga shared virtual address memory space in accordance with an example fOCTdevice. The system includes a plurality of processors 302 a-f that canaccess a shared memory subsystem 304. The system incorporates aplurality of programmable hardware memory algorithm processors (MAPs)306 a-f in the memory subsystem 304. Each MAP 306 a-f can comprise amemory 308 a-f and one or more field programmable gate arrays (FPGAs)310 a-f The MAP provides a configurable functional unit and particularalgorithms or portions of algorithms can be provided to the FPGAs 310a-f for processing in close coordination with a respective processor.For example, the MAPs can be used to evaluate algebraic expressionsregarding the data model and to perform adaptive data restructuring inexample examples. In this example, each MAP is globally accessible byall of the processors for these purposes. In one configuration, each MAPcan use Direct Memory Access (DMA) to access an associated memory 308a-f, allowing it to execute tasks independently of, and asynchronouslyfrom, the respective microprocessor 302 a-f In this configuration, a MAPcan feed results directly to another MAP for pipelining and parallelexecution of algorithms.

The above computer architectures and systems are examples only, and awide variety of other computer, cell phone, and personal data assistantarchitectures and systems can be used in connection with exampleexamples, including systems using any combination of general processors,co-processors, FPGAs and other programmable logic devices, system onchips (SOCs), application specific integrated circuits (ASICs), andother processing and logic elements. In some examples, all or part ofthe computer system can be implemented in software or hardware. Anyvariety of data storage media can be used in connection with exampleexamples, including random access memory, hard drives, flash memory,tape drives, disk arrays, Network Attached Storage (NAS) and other localor distributed data storage devices and systems.

In example examples, the computer system can be implemented usingsoftware modules executing on any of the above or other computerarchitectures and systems. In other examples, the functions of thesystem can be implemented partially or completely in firmware,programmable logic devices such as field programmable gate arrays(FPGAs) as referenced in FIG. 31, system on chips (SOCs), applicationspecific integrated circuits (ASICs), or other processing and logicelements. For example, the Set Processor and Optimizer can beimplemented with hardware acceleration through the use of a hardwareaccelerator card, such as accelerator card 122 illustrated in FIG. 29.

VI. Terminology

The terminology used therein is for the purpose of describing particularexamples only and is not intended to be limiting of a device of thisdisclosure. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. Furthermore, to the extent that the terms“including”, “includes”, “having”, “has”, “with”, or variants thereofare used in either the detailed description and/or the claims, suchterms are intended to be inclusive in a manner similar to the term“comprising”.

Several aspects of a device of this disclosure are described above withreference to example applications for illustration. It should beunderstood that numerous specific details, relationships, and methodsare set forth to provide a full understanding of a device. One havingordinary skill in the relevant art, however, will readily recognize thata device can be practiced without one or more of the specific details orwith other methods. This disclosure is not limited by the illustratedordering of acts or events, as some acts may occur in different ordersand/or concurrently with other acts or events. Furthermore, not allillustrated acts or events are required to implement a methodology inaccordance with this disclosure.

Ranges can be expressed herein as from “about” one particular value,and/or to “about” another particular value. When such a range isexpressed, another example includes from the one particular value and/orto the other particular value. Similarly, when values are expressed asapproximations, by use of the antecedent “about,” it will be understoodthat the particular value forms another example. It will be furtherunderstood that the endpoints of each of the ranges are significant bothin relation to the other endpoint, and independently of the otherendpoint. The term “about” as used herein refers to a range that is 15%plus or minus from a stated numerical value within the context of theparticular usage. For example, about 10 would include a range from 8.5to 11.5.

EXAMPLES Example 1

This example describes a method to measure and analyze OCT signals toestimate optical absorption properties of whole blood. In vivo retinaloximetry by vis-OCT (fOCT comprising visible light) was performed, usinga comprehensive analytical model describing both the scattering andabsorption from whole blood, as well as blood vessel scattering. Thepacking factor due to multiple optical scattering by blood cells wasalso included in this model.

The principle of vis-OCT oximetry is illustrated in FIG. 12. Theincident light reflected from the bottom vessel wall double-passed thevessel lumen. The spectrum of reflected light was extracted by a seriesof short-time Fourier transforms (STFT), which was formulated as:

I ² =I ₀ ² R ₀ rexp[−2ndμ _(HbO2)(sO₂)−2nd _(Hb)(1−sO₂)],

where I₀ is the incident intensity on the retina. The opticalattenuation by ocular lens and vitreous chamber were ignored and thusthe source spectrum was taken as I₀; R₀ is the reference armreflectance; n is the mean refractive index of the blood (˜1.35); d [mm]is the vessel diameter; r [dimensionless] is the reflectance at thevessel wall, whose scattering spectrum can be modeled as a power lawunder the first-order Born approximation r(λ)=A λ^(−a) where A is aconstant. The optical attenuation coefficient μ [mm⁻¹] combines theabsorption (μ_(a)) and scattering coefficients (μ_(s)) of whole blood,which are both wavelength- and oxygenation-dependent. The subscripts Hband HbO₂ denote the contribution from deoxygenated and oxygenated blood,respectively. By taking the natural log and plugging in the aboveexpressions, Eq. 1 becomes

${\ln \left( \frac{I(\lambda)}{I_{0}(\lambda)} \right)} = {{- {{nd}\left\lbrack {{{sO}_{2} \cdot {\mu_{{HbO}\; 2}(\lambda)}} + {\left( {1 - {sO}_{2}} \right) \cdot {\mu_{Hb}(\lambda)}}} \right\rbrack}} - {\frac{1}{2}\alpha \mspace{14mu} {\ln (\lambda)}} + {\frac{1}{2}{{\ln \left( {AR}_{0} \right)}.}}}$

A least-squares (LS) fit can then be performed to fit the spectrum andobtain sO₂, a, and ln(AR₀). The spectra of 11 is equal toμ=μ_(a)+Wμ_(s), where W is blood cell packing factor that weights thescattering spectrum.

In this example, the setup consisted of a free-space spectral-domain OCTsystem FIG. 1, implemented with a supercontinuum source (SuperK, NKTphotonics). The spectral range was centered at 585 nm with an 85-nm FWHMbandwidth. The theoretical axial resolution was 1.5 μm in air and wasmeasured to be 1.7 μm. A 2k pixel line scan CCD (Aviiva, SM2, e2v) wasused in a home-made spectrometer. The A-line rate was 24 kHz. To acquirea 3D image consisting 256×256 A-lines, the acquisition time was 2.7 s.Pigmented rats were imaged (Long Evans rat, 500 g, Harlan Laboratories)for in vivo experiments.

vis-OCT data was performed with the following steps. The raw spectrawere first normalized by the source spectrum and the DC components weresubtracted. After 3D images were acquired, the fundus image was obtainedby mean intensity projection and the center line of each blood vesselwas digitally identified. Finally, OCT spectra were extracted from thebottom vessel wall along the center lines by STFT with a Gaussian windowsize k_(w)=0.32 μm⁻¹ (17 nm at 585 nm), relaxing the axial resolution(in air) to ˜8.9 μm. The spectra was averaged from each vessel for arobust estimation, and applied LS from 540 to 610 nm to retrieve sO₂.

How blood optical scattering and blood cell packing factor affect thespectrum of μ was observed. According to the Kramers-Kronigrelationship, the absorption of hemoglobin affects blood opticalscattering, and thus causes an oxygenation-dependent optical scatteringspectrum. The spectra of μ_(a) and μ_(s) was calculated from oxygenatedand deoxygenated blood as previously described, with plasma refractiveindex set at 1.35. Furthermore, due to multiple scattering effects ofdensely packed blood cells, the scattering coefficient in whole bloodwas weighted by a packing factor W (0≤W≤1). The expression of iscorrected as μ=μ_(a)+Wμ_(s), where W depends on the volume fraction ofthe red blood cells in whole blood (hematocrit) H. Thus, the spectrum ofμ is a function of W. With increasing packing factor, the spectrum of μred-shifted and the entire spectral shape altered as well. The value ofW was varied from 0 to 1 and LS fit was performed, while the mean valueand standard deviation of sO₂ from the major arteries and veins wereplotted. The mean spectral residuals from LS fit for every vessel werealso calculated. All the mean residuals for arteries and veins wereaveraged (FIG. 10). When W=0.2, the variation of calculated oxygenation(error bar) from both arteries and veins reached their minima as well asthe fitting residuals. The fitting resulted from an artery and vein (No.3 and No. 6 in FIG. 11) and were sampled. When W=0.2, the hematocrit wascalculated as 35% in the cylindrical particle model, 30% in thespherical particle model. FIG. 11 showed in vivo results of vis-OCToximetry. An OCT fundus image is displayed in grayscale (FIG. 11) ininversed contrast. The bright blood vessel structure corresponds to thestrong optical attenuation in blood. As a comparison, we sectioned the3D OCT volume from depth range 160-250 μm (correspond to the IS/OSjunction to the RPE layer) and projected the mean intensity. As aresult, the contrast from the microvasculature was enhanced (FIG. 16).Also, mean sO₂ values in major vessels were quantified and thepseudo-color map of sO₂ was overlaid in FIG. 16. A circular scanningpattern around the optic disk was used (the circle in FIG. 16) with 4096A-lines, so that all the major vessels could be sampled. We expanded thecircular scan into a B-scan image where the vessel index corresponds tothe numbers in FIG. 18. The values of sO₂ in individual vessels aregiven with red and blue color labeling arteries and vein (FIG. 17). Onaverage, sO₂ from arteries and veins were 95±3% and 72±7%, respectively.The standard deviation from the veins was higher than for arteries,which was mostly caused by the flatter spectrum of μ. The alternatingartery and vein pattern can be confirmed by the size of the vessels(i.e. arteries have smaller diameter than veins due to theircontractility).

The algorithm and model proposed herein were based on the fact that thebottom blood vessel wall can be imaged with a high signal to noise ratio(SNR). In the current example, sufficient SNR for sO₂ was achieved withcalculation in vessels with diameters between 30 μm to 130 μm.

Example 2

This example demonstrated that visible-light optical coherencetomography (vis-OCT) can quantify rMRO₂ in vivo through the concurrentmeasurement of the blood flow and sO₂ from retinal circulation. The 3Dimaging capability allowed vis-OCT to recover optical spectraspecifically from blood vessels and eliminate the confounding signalfrom other retinal layers. The rMR0₂ was obtained by combining the sO₂measurement with the OCT flow measurement. The blood flow and sO₂measurements were validated both in vitro and in vivo. As proof ofprinciple, we investigated the metabolic response to progressive hypoxiachallenges and changes in the balance between the retinal and choroidalcirculations during hypoxia. The experimental results werecross-validated by an oxygen-diffusion model derived from directmeasurements of the oxygen tension profile in rat outer retina usingmicroelectrodes.

The 3D structure of the rat retina was imaged and rMRO₂ quantified usingvis-OCT (FIG. 22). A focused broadband laser was scanned across theretina to provide transverse (x,y) discrimination. The reflectance atdepth (z), A-line, was reconstructed by the interference between theillustrated light and the reference light. Each 3D measurement (2.8 mmby 2.8 mm by 1 mm in x, y, z) took only several seconds (typically 2.5s) with 98 fps frame rate, allowing monitoring of rMRO₂ with hightemporal resolution. To quantify the rMRO₂ (gas volume of oxygenconsumed per unit time, mL/min), two parameters were measured from theretinal circulation: total retinal blood flow F [JIL/min] and relative502 [percent]. The rMRO₂ was calculated according to the followingequation:

rMRO ₂=1.34×C _(H) _(b) ×F×(s _(a)O₂ −s _(v)O₂),

where C_(Hb) is the hemoglobin concentration [g/JIL], and 1.34 is theoxygen-binding capacity of hemoglobin [mL/g]. The subscript of a and vdenotes arterial and venous sO₂. Blood flow is the product of thecross-sectional vessel area (s) and velocity (v), where s was calculatedfrom the tomographic image and v was measured based on the phasevariation from the moving blood cells as described herein. The contrastfor sO₂ is from the distinct absorption spectra from oxy- anddeoxyhemoglobin. By fitting the blood spectra extracted from bloodvessels, the percentage of oxyhemoglobin in total hemoglobin (sO₂ bydefinition) was calculated.

Because of the strong attenuation of blood in the visible-light range, ashadow was cast underneath the vessels when the light passed by. An enface slice was used in deep retina as a screen to capture this “shadoweffect” and create a 2D “print” of the microvasculature. The largeretinal vessels were visualized clearly as well as the details of thecapillary network. This method does not require a high-density scanningprotocol as reported previously, and yet it provides robust label-freemicroangiography.

To Test the accuracy of sO₂ and blood flow measurements, flowcalibration in vitro was performed, where a turbid aqueous solution (1%intralipid) was pumped through a capillary tube by syringe pump, andthen the vis-OCT flow measurement was calibrated against the pump flowsettings. For sO₂, bovine whole blood with controlled sO₂ flowed throughthe capillary tube and we compared the vis-OCT sO₂ quantification withthe results derived from blood analyzer readings. The accuracy waswithin 0.25 f.l/min and 4% for velocity and sO₂ measurements,respectively.

To accomplish the flow measurement in vivo, a dual-circle scanningpattern was adopted around the optic nerve head (ONH). Because retinalblood vessels run radially from the ONH, each circle crossed all of thearteries and veins and allowed capture of total retinal blood flow (FIG.21). The displacement of vessels between the two circular scans providedthe vessel directionality for absolute flow. Eight dual-circle scanswere performed with an A-line rate of 70 kHz. The high-speed scanningallowed capture of the pulsatile profile of the blood flow (FIG. 21). Asimultaneous EKG recording was referenced to provide the timing of thecardiac cycle. The pulsatile flow pattern from an artery coincided wellwith the EKG profile, with a slight delay (˜0.1 s) between the peaks ofthe flow and the QRS complex. This delay was caused by the time taken bythe sequence of atrioventricular node discharge, ventricularcontraction, and the pressure propagation from heart to head. A Fouriertransform of the pulsatile profile was taken and the distinct peaks fromall the arterial flows were consistent, indicating that the heart ratewas 4.36 s⁻¹. The flow readings over the eight dual-circle scans foreach vessel were averaged and summed total arterial and venous flows.The total blood flows from the arterial and venous vessels were withinmeasurement precision (±0.38f.L/min averaged from five rats)

To verify the consistency of the inward and outward blood flow, thevalue of total averaged blood flow was calculated at 6-8 JIL/min (n=5rats), which agreed well with the reported data using the sameanesthesia protocol.

Two experimental protocols were used to examine the accuracy of our invivo sO₂ measurement. In the first protocol, oxygen content wasgradually changed in the inhaled air from 21% to 10% in several steps.After each adjustment, the animals were allowed to adapt to the changedair and re-stabilize for ˜2 mins. The systemic peripheral arterialoxygenation (spO₂) was monitored by a pulse oximeter attached to the ratrear leg. At each inhalation condition, arterial sO₂ was measured byvis-OCT and compared TO the averaged values with the pulse oximeter spO₂readings (FIG. 23). The linear correlation (R2=0.839) established theresponsiveness of our sO₂ measurements to the blood oxygenation changes.In the second protocol, the inhaled oxygen was changed from 21% to 100%,and then from 21% to 10% (FIG. 23). Arterial sO₂ was roughly unchangedfrom 21% to 100%, but dropped significantly at 10% oxygen (0.95±0.02 at21% oxygen, 0.95±0.01 at 100% oxygen, 0.96±0.01 at recovery 21%, and0.59±0.03 at 10% oxygen); on the other hand, the venous sO₂ changed withthe changing oxygen content (0.75±0.03 at 21% oxygen, 0.86±0.01 at 100%oxygen, 0.74±0.02 at recovery 21%, and 0.48±0.01 at 10% oxygen).

A critical factor for any longitudinal study is the stability ofmeasurements repeated over time. In order to test the repeatability, atime course experiment was performed in which five measurements weretaken for the same subject over the span of two weeks. The standarddeviations of various parameters for the five measurements were allwithin 11% of the mean values (7.4% for arterial sO₂, 6.4% for venoussO₂, 9% for blood flow, and 11% for rMRO₂).

Having characterized the accuracy of blood flow and sO₂ measurement,systemic oxygen tension and how it affects rMRO₂ during hypoxia wasstudied. Although previous studies have shown hemodynamic (increasedretinal blood flow) and vascular changes (increased vessel diameter)under low oxygen supply, the comprehensive observation of how innerretinal oxygen consumption reacts to limited oxygen supply has neverbeen reported. In addition, the retinal circulation provides very littleoxygen to the outer retina under light-adapted conditions, but how thischanges during hypoxia had not known.

The retinal vascular changes under hypoxia were observed (FIG. 22) Themajor arteries and veins dilated during hypoxia. The average vesseldiameter increased by ˜35% for arteries (59.7±1.5 f.m during normoxia,80.8±2.0 f.m during hypoxia), and ˜16% for veins (77.4±2.0 f.m duringnormoxia, 90.2±2.3 f.m during hypoxia). In normoxia, the arteries werecurved due to a constrictive vascular tone; under hypoxia, straighterarteries indicated relaxation of vascular smooth muscle. In addition,the dilation could also be observed in smaller arterioles (FIG. 22),which allows more blood flow into the deep retinal capillary network inthe outer plexiform layer (OPL).

In order to progressively track the auto-regulatory response, a“step-down” hypoxia challenge protocol was performed, in which theinhaled oxygen content was reduced from 21% (normoxia) to 9% (hypoxia)in six steps (21%, 19%, 16%, 14%, 11% and 9%) (FIG. 23). Themeasurements were taken at each step and the progressing trends of sO₂,blood flow, vessel diameter, and rMR O₂ were quantified (n=6 rats). Theentire experimental protocol took less than 30 min.

As expected, both arterial and venous sO₂ decreased with the reducedoxygen (FIG. 19). The venous sO₂ decreased almost linearly, while thearterial sO₂ decreased more quickly when the oxygen content was below14%. Because the oxygen partial pressure (PO₂) may be the directstimulus to autoregulation and has more biological meaning, sO₂ readingswere translated to PO₂ based on the hemoglobin dissociation curve,defined by Hill's equation with n=2.8 and P50=32.9. For arteries andveins, the average PO₂ was 106.5±6.6 and 45.5±1.8 mmHg, respectively,and dropped almost linearly to 36.8±1.5 and 26.3±0.9 mmHg with 9%inhaled O₂. The arteriovenous sO₂ difference exhibited a two-segmentpattern that increased slightly when the arterial PO₂ was higher than 65mmHg and decreased quickly thereafter. When examined, the progressivetrend of vessel diameter with arterial PO₂, also had a similartwo-segment pattern where the dilation became more dramatic duringsevere hypoxia. A consequence of vessel dilation was the reduction invascular resistance, which allowed more blood flow (FIG. 23). Theincreased blood flow compensated for the deficiency in saO₂, and thetotal oxygen delivery (defined by 1.34×F_(artery)×saO₂) by arterialvessels was maintained (slope=−0.0028). The oxygen extraction fraction(defined by the ratio of arteriovenous sO₂ difference over arterial sO₂)increased, indicating that the retina extracted oxygen more efficientlyunder hypoxia. Finally, the oxygen consumption by the retina from theretinal circulation also increased with the decreased arterial PO₂ (FIG.23). The slopes in FIG. 23 are significantly different from zero(P=0.033, 0.001 and <0.001, respectively), with the scatter contributedlargely by the vertical offset of the data for individual animals, eachof which exhibited the same trend in slope (illustrated in the inset toFIG. 23i ).

vis-OCT was used to accurately measure rMRO₂ and visualize themicrovasculature. This method allowed monitoring of retinal function viaits oxygen consumption with high temporal resolution. The response ofrMRO₂ to the systemic PO₂ changes and observed increased oxygenconsumption from the retinal circulation under hypoxia were measuredwith high accuracy.

The increased extraction of oxygen during hypoxia may be a result of theincreased oxygen supply to the outer retina from retinal circulationwhen the oxygen supply from the choroidal circulation falls. Thisbalance between the retinal and choroidal circulations may not have anactive compensation during hypoxia; rather, it may result from thedifferent ways in which the two circulations behave in response tooxygen deficiency. The choroidal circulation has a small arteriovenoussO₂ difference and very little autoregulatory response, while theretinal circulation has a large arteriovenous sO₂ difference and is wellregulated. When the systemic PO₂ decreases, the oxygen supply from thechorioicapillaris falls, reducing the PO₂ around photoreceptors andincreasing the gradient to drive oxygen toward the photoreceptors fromthe retinal capillaries in the OPL (FIGS. 24a-d ). To determine whetherthis balancing mechanism could quantitatively account for the increasedoxygen extraction from the retinal circulation, we conducted asimulation.

The outer retina is avascular and its oxygen supply solely depends ondiffusion. Anatomically, the outer retina can be divided further intothree layers (FIGS. 24a-d ). From the choroidal side, they arephotoreceptor outer segments (OS, Layer 1), photoreceptor inner segments(IS, Layer 2), and the outer nuclear layer (ONL, Layer 3). The retinaloxygen profile across the outer retina has been characterized bymicroelectrode measurements in various mammalian species, including rat(FIG. 19). The PO₂ is maximal at the choroid and falls with a steepgradient towards the inner segment of the photoreceptors, where oxygenis consumed. In the outer nuclear layer, PO₂ also exhibited a gradienttoward the inner segment of the photoreceptors. This oxygen profile canbe modeled by a one-dimensional three-layer diffusion model based onFick's second law,

${Q = {{Dk}\frac{d^{2}P}{d^{2}x^{\prime}}}},$

where Q is oxygen consumption normalized by the tissue weight[ml·min·⁻¹·100 g⁻¹], D is diffusivity of oxygen [1.97e-5 cm²/s], k issolubility of oxygen [2.4 ml O₂/(ml retina·mmHg)], P is P O₂ [mmHg], andx is the distance from the choroid. By fitting the diffusion model tothe measured P O₂ curves, the average oxygen consumption in outer retinaQ_(av) under light adaption has been characterized. In addition, thefraction of Q_(av) provided from the retinal circulation also can becalculated given the thickness of the three layers in the outer retina,PO₂ values at boundaries of the outer retina, and Q_(av). Usingparameter values measured from rat retina, and assuming that choroidalPO₂ decreased, hypoxic profiles were simulated across the outer retina.This allowed us to estimate the additional oxygen that would be providedto the outer retina by the retinal circulation and compare it with ourexperimental data. The changes in retinal oxygen extraction withdecreased arterial P O₂ were almost identical (slope=−0.0020 and−0.0023) in the simulation and the experiment, respectively.

Example 3

The ability to quantify rMRO₂ with fOCT and vis-OCT can provide valuableinsight into the pathogenesis of various retinal diseases, particularlyDR and glaucoma. A key element is understanding the causal relationshipbetween retinal cell degeneration and hemodynamic dysregulation. Forexample in DR, it is known that endothelial and pericyte disruptionoccurs in early-stage DR, but the hemodynamic changes that occur areunclear. Some studies showed increased retinal blood flow and suggestedthat the higher blood flow and high glucose level causes hyperperfusion,which further damages the endotheliuam and pericytes; however,contradicting data exist that show decreased blood flow is one of theearliest changes in the diabetic retina. The hypothesis is that the lossof pericytes in the early phase of the disease reduces oxygenconsumption, which may paradoxically lead to increased oxygenation ofthe retina. This might create a relative hyperoxia, resulting invasoconstriction and reduced blood flow. Similarly, in glaucoma, thereis degeneration of retinal ganglion cells and their axons. Althoughaltered blood flow and vasculature were observed in glaucoma, theircausal relationship to ganglion cell death remains unknown. A fOCTdevice configured for retinal scanning is setup to diagnose, monitor antreat patients for a variety of ophthalmic diseases. By measuring rMRO₂,metabolic function and blood flow is measured and related to a number ofdiseases where the retina experience a change in oxygen consumption as aresult of disease or susceptibility to disease. The connection betweenhemodynamic dysregulation and retinal cell degeneration. With improvedunderstanding of retinal metabolic function, improved approaches toearly disease detection and therapeutic strategies can be designed.

Example 4

In this example, a probe configured with vis-OCT measurements wasconfigured to image endocervical mucus and potential interaction withinfectious disease such as HIV. Despite the current methods usingexogenous substances to prevent AIDS infection (e.g., vaginal barrierdevices and antibiotics), there are more and more investigations focuson the intrinsic AIDS defending systems. Among them, endocervical mucusserves as an important barrier. Consisting of various glycoprotein andantibodies, the normal mucus is very effective at trapping andneutralizing invading infectious microbes.

One critical parameter indicating the integrity of the endocervicalbarrier is the mucus thickness, which is still challenging to monitor todate, partially because its gel-like appearance prevents directmeasurement by visual inspection. In this study visible light opticalcoherence tomography (vis-OCT) was to dynamically measure the mucusthickness in vivo with lateral resolution and micrometer-scale depthresolution. The mucus contained intrinsic contrast originating from thecell debris and undissolvable substance, whose characteristicback-scattering pattern differentiates it from underlying tissue,allowing quantitative measurement of its thickness. Vis-OCT was capableof visualizing and performing endocervical mucus thickness measurementsex vivo. Also the vis-OCT probe achieved real-time dynamic monitoring ofmucus secreting and hydrolysis. The vis-OCT system was successfullyminiaturize for an endoscopic probe that can was easily inserted intomacaque FRT.

A prototype endoscopic OCT probe was constructed that can perform linearand circular scans. To achieve higher penetration depth for in situmeasurement, near infrared (NIR) light source was also used. Theendoscopic probe was a fiber-based, miniature sized lens-prism complex.The schematic diagram of the OCT probe was shown in FIG. 26. Agradient-index (GRIN) lens was used to obtain light focusing. Aright-angle prism is attached on the GRIN lens to achieve desiredside-view imaging. The lens-prism complex is mounted on a rotatingshaft, which was driven by a step motor to control the circular scan. Amotorized linear translation stage was used to move the probe from theproximal to distal position, allowing a 3-dimensional cylindricalscanning pattern to be performed. The photo in FIG. 26 shows thedimension of a finished prototype endoscopic OCT probe. The outerdiameter of the probe was roughly 4.5 mm, which can be easily insertedinto the macaque FRT.

FIG. 27 shows a cross sectional B-scan frame using the bench top OCTsystem. Endocervical tissue structures including epithelium and laminapropria (LP) were visualized in OCT images. Mucus was recognized by astrong reflection from mucus surface and scattered cell debris withinmucus.

The relative mucus thickness change when cultured with PBS was plottedin FIG. 27. During the imaging sequence, a nearly linear increase ofmucus thickness within the first 30 minutes of the procedure wasobserved with up to threefold thickness. The change in the thickness wasstatistically significant for these time points (P<0.01). The mucusthickness reached a plateau thereafter.

A 360° cylindrical scan was performed of the intact macaque vagina ductex vivo. FIG. 28 shows one of the rotational B-scan images of the entire3-dimensional volumetric dataset. The image was rescaled to enlarge thetissue layers for better visualization, showing the rough surface of thevaginal mucosa. We also conducted a high-resolution volumetric scancovering a scanning angle of 45° (corresponds to 1.2 mm circumference)and 0.8 mm longitudinal displacement. FIG. 28 shows one of the B-scan ofthe volumetric data. Besides some of the flattened surface caused by thepressure asserted by the protective glass shell, anatomical structuressuch as vagina rugae were visualized. In addition, the lightenedgranular pattern in the recess of epithelium indicated the presence ofvaginal mucus. The probe was used to show dynamic properties of mucalflow and tissue integrity which could be used for down stream diagnosticand disease monitoring purposes, such as for HIV infection.

Example 5

In one example, a colonoscopy probe or endoscope is adapted for fOCT toevaluate the intestinal wall polyps for cancer. Currently, various otherimaging techniques are used in conjunction with endoscopic imaging;however, the approach provides poor sensitivity and specificity. Yet,all cancers are known in the art to be highly vascular due toangiogenesis. Angiogenesis is a process of new blood vessel growth frompreexisting blood vessels. Angiogenesis is a fundamental step of tumorsfrom a dormant state to a malignant state, with new blood vesselspenetrating into cancerous growths and supplying nutrients and oxygen.Since blood vessels carry hemoglobin, a fOCT enabled probe is able toprovide a highly accurate measurements of oxygen consumption as functionof blood flow rate and hemoglobin oxygen saturation. Metabolic rate ofone or more polyps is calculated as provided by the methods herein.Additionally, the fOCT probe is able to image with high resolution,various aspects of the vasculature underneath or around a polyp to helpdetermine if the polyp may be pre-cancerous or cancerous at an earlierstage. It is generally known in the art that cancers have enhancedmetabolic properties compared to normal tissues, so then cancerous cellshave higher oxygen content from hemoglobin and a greater concentrationof deoxygenated hemoglobin compared to normal tissues. Alternatively,when imaging potential colon cancer polyp with fOCT, comparing the fOCTimages and metabolic rate calculations to what a fOCT of normal tissuelooks like; diagnosis is possible if increase blood vessel formationappears in the fOCT image. Abnormal blood vessel formation could also beindicative of diseased tissue. For example, abnormal vascular patternscould be indicative of angiogenesis and putative colon cancer. Abnormalvascular patterns would be any vascular patterns outside the normalvasculature anatomy of the health colon tissue.

Example 6

Another example of cancer diagnosis would include breast cancer. A fOCTprobe is configured for in a needle and for a surgical tool for use inthe removal of the breast cancer tumor. With the needle fOCT probe, theneedle is to be placed at sites around the suspected area of the tumorto examine the morphology of the tissue and the tumor's vasculature. 3DfOCT images combined with metabolic rate information of one or moreareas of the breast help the surgeon determine optimal surgical marginsfor excision of the breast cancer tumor. Oxygenated hemoglobin moleculeswhich have increased due to angiogenesis may be indicated to the surgeonby higher metabolic rate as determined and calculated by fOCT methods.The cancerous cells in the breast with the higher oxygen content fromhemoglobin and a greater concentration of deoxygenated hemoglobin couldbe imagined and diagnosed accordingly, when compared to normal breasttissue. Alternatively, when imaging the breast with fOCT, comparing theultrasound image to what a fOCT image of normal tissue, diagnosis ispossible if increased or abnormal blood vessel formation appears.

Example 7

Another example of fOCT, includes configuring methods and devices fordiagnostic techniques for diseased tissue with increased blood vesselformation, which could be detectable by with fOCT. Angiogenesis is knownto occur during coronary artery disease, peripheral artery disease, andstroke when there's insufficient blood supply. For example, the bloodvessels that surround large arteries or perfuse large arterial walls,such as vaso vasorum. These vessels surround the artery around theheart. If there is a plaque in these blood vessels, then the bloodsupply grows as the plaque size increases, and more cells from theseadditional blood vessels move into the plaque, making it unstable andmore likely to rupture causing heart attacks and strokes. It has beenshown that the endothelium of the vaso vasorum is disturbed inhypercholesterolemic conditions. This induces constriction of the vasovasorum with subsequent lack of oxygen supply. Subsequently VEGFexpression will increase with rapid vaso vasorum vessel formation as aconsequence. Such increased blood vessel formation could be detectableby described systems herein, as to diagnose susceptible myocardialinfarction or ischemic conditions.

Example 8

In this example, fOCT is configured for a probe to be inserted into acatheter, which is directed to the site of an aneurysm. The fOCT probeis able to take successive measurements of the metabolic rate andprovide 3D structural images of vessels in and around the aneurysm,informing the surgeon where to operate in an optimally safe place. ThefOCT probe is used to guide one or more surgical instruments to theaneurysm site in need of treatment.

Example 9

In this example, fOCT is configured for an intraoperative tool for useto analyze blood vasculature in the brain to help surgeons identify fociof abnormal neural activity. In the treatment of epilepsy,neuromodulation of one or more epileptic foci may be necessary tocontrol epileptic symptoms. In order to identify foci, surgeons use thefOCT probe to identify regions in the brain with abnormal vasculatureand increased metabolism, which may correlate with abnormal neuralactivity associated with epilepsy. Using fOCT data, surgeons identifyepileptic foci and apply treatment.

Example 10

In this example, fOCT is used to monitor the treatment and prognosis ofa patient with AMD. A patient presents symptoms of early stage AMDincluding the presence of drusen and sporadic blurriness and blackpatches in vision. A doctor administers Lucentis®, an FDA approved drugand anti-VEGF drug. The patient's retina is monitored with fOCT beforeand after administration. After 3 weeks, little to no effect is observedwith Lucentis®. The doctor switches treatment and administers anotheranti-VEGF drug, Eyelea® to the patient. The patient's retina ismonitored before and after administration of the drug.

What is claimed is:
 1. A method for evaluation of a treatment strategyfor a subject, the method comprising: a. obtaining three dimensional(3D) optical coherence tomography (OCT) scans of a target of thesubject; b. determining a status of one or more molecular markers in abodily fluid in the target and simultaneously quantifying flow of thebodily fluid from the 3D OCT scans generated by the obtaining of 3D OCTscans of the target in a single measurement; and c. evaluating one ormore treatment options by comparing the status of one or more molecularmarkers in the bodily fluid in the target to a reference to drive amedical decision.
 2. The method of claim 1, wherein the determining thestatus of one or more molecular markers includes determining metabolicactivity or a change in metabolic activity in the target.
 3. The methodof claim 1, wherein the determining the status of one or more molecularmarkers includes determining oxygen saturation.
 4. The method of claim1, wherein the comparing the status of one or more molecular markers inthe target in the bodily fluid to the reference is used to determine achange in target function.
 5. The method of claim 1, wherein thedetermining a status of one or more molecular markers in a bodily fluidin the target is performed by measuring an intensity, amplitude or phaseof visible light reflected at a plurality of depths for each OCT scanobtained of the target.
 6. The method of claim 1, wherein the evaluatingone or more treatment options includes stratifying one or more treatmentoptions using an algorithm-based approach.
 7. The method of claim 6,wherein the evaluating one or more treatment options is performed usinga computer and a computer readable medium.
 8. The method of claim 6,wherein the stratifying one or more treatment options using analgorithm-based approach comprises generating a report containinginformation predicting efficacy of one or more treatment options in thetarget.
 9. The method of claim 6, wherein the stratifying one or moretreatment options using an algorithm-based approach includes generatinga report containing a recommendation of one or more treatment options.10. The method of claim 6, wherein the stratifying one or more treatmentoptions incorporates a type of disease, an age of the subject, a statusof drug metabolism genes, and a family medical history for the subject.11. The method of claim 1, wherein the target is selected from thefollowing group: diseased tissue, suspected diseased tissue, previouslytreated tissue, and healthy tissue.
 12. The method of claim 1, whereinthe evaluation of one or more treatment options includes at least one ofchanging a dosage of one or more drugs, selecting a frequency of drugadministration, making a drug selection, or changing a drug selection.13. The method of claim 1, wherein the evaluation of one or moretreatment options includes assessing candidate molecules for potentialefficacy, toxicity and dosing in the target.
 14. The method of claim 1,wherein the reference includes at least one of a healthy image, anaverage of information from healthy subjects, or OCT images generated ata different time.
 15. The method of claim 1, wherein the referenceincludes scientific information curated in a database and used forcomparison across select patients or sub groups of patients.
 16. Themethod of claim 1, wherein the determining a status of one or moremolecular markers in a bodily fluid in the target, while simultaneouslyquantifying flow of the bodily fluid indicates the presence or absenceof disease.
 17. The method of claim 1, wherein the target is selectedfrom the group consisting of tissue, healthy tissue, diseased tissue,retina, tumor, cancer, growth, fibroid, lesion, skin, mucosal lining,organ, graft, blood supply and one or more blood vessels.
 18. The methodof claim 1, wherein the determining the status of one or more molecularmarkers includes imaging a blood flow or a blood supply.
 19. The methodof claim 1, wherein the obtaining 3D OCT scans of a target is performedwith visible-light or invisible light.
 20. A system for the evaluationof a treatment, the system configured to: a. obtain three dimensional(3D) optical coherence tomography (OCT) scans of a target; b. determinea status of one or more molecular markers in a bodily fluid in thetarget and simultaneously quantify flow of the bodily fluid from the 3DOCT scans generated by the obtaining of 3D OCT scans of the target in asingle measurement; c. evaluate one or more treatment options bycomparing the status of one or more molecular markers in the target inthe bodily fluid to a reference with a computer using a computerreadable medium to drive a medical decision.